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Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist with deep expertise in antibody process development and manufacturing to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be an expert in making antibodies, with hands-on experience expressing, purifying, characterizing, and formulating them, from small screening batches to material for IND-enabling studies. Above all, you'll close the loop between AI-generated hypotheses and experimental data to share with the community. Working alongside AI researchers and engineers, you'll build and run the workflows that turn AI-designed sequences into well-characterized protein, and pressure-test AI predictions of expression, stability, and manufacturability against real data. This role is fully on-site in the San Francisco Bay Area. Key responsibilities Develop and run expression and purification processes for antibodies and other recombinant proteins end to end, including transient and stable expression in mammalian cells (HEK293, CHO), affinity capture (Protein A, IMAC), polishing chromatography, buffer exchange, and formulation Characterize what we make with the right analytical panel, for example SEC, CE-SDS, icIEF, LC-MS (intact mass, peptide mapping, glycans), DLS, thermal stability, endotoxin, and binding kinetics (SPR, BLI) Build the laboratory for this work, including selecting, installing, and qualifying equipment and setting up workflows that scale from plate-based production of hundreds of designs to gram quantities of a lead Evaluate AI-designed antibodies for manufacturability (titer, aggregation, stability under stress, viscosity, chemical liabilities), drive them to experimental readout, and feed results back to research teams Plan the chemistry, manufacturing, and controls (CMC) path toward IND-enabling studies, from cell line development and scale-up to analytical methods and stability, and coordinate technology transfer and manufacturing with external contract manufacturers Ensure experimental data across programs is high quality and well documented, including batch records, methods, raw data, and failure modes Communicate findings clearly to biology, AI research, and life sciences audiences Minimum qualifications PhD in biochemical engineering, chemical engineering, biochemistry, or a related field Demonstrated experience in process development and manufacturing of antibodies or other recombinant proteins, including material supplied for IND-enabling or clinical studies, with recent, sustained hands-on laboratory work Comfort navigating ambiguity and defining problems in a rapidly evolving research environment Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills Preferred qualifications 5+ years of biologics process development experience beyond the PhD Depth in both upstream (cell line development, bioreactors) and downstream (chromatography, filtration) development, with working knowledge of analytical and formulation development Experience setting up a protein production or process development laboratory, including laboratory automation and high-throughput, plate-based expression and purification Experience directing technology transfer and GMP manufacturing at contract development and manufacturing organizations, with contributions to the CMC sections of an IND Statistics or coding skills, for example design of experiments or Python for data analysis and automation Experience using AI or ML tools in the life sciences Publications and/or patents demonstrating scientific impact The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist with deep expertise in therapeutic antibodies to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be an expert in antibody design and engineering who has taken antibodies through the whole process, from target selection and lead optimization to candidate selection and IND-enabling studies. Above all, you'll close the loop between AI-generated hypotheses and experimental data to share with the community. Working alongside AI researchers and engineers, you'll drive antibody programs end to end and pressure-test AI-designed antibodies against the bar a real drug candidate has to clear. This role is fully on-site in the San Francisco Bay Area. Key responsibilities Design and engineer therapeutic antibodies and oversee programs end to end, including target and epitope selection, choice of format (IgG, Fab, scFv, VHH, bispecific), humanization, affinity maturation, Fc engineering, and candidate selection Define the screening cascade for each program, from binding kinetics (SPR, BLI), epitope binning, and species cross-reactivity to cell-based functional assays and developability (expression, aggregation, polyreactivity, stability, viscosity, immunogenicity risk) Plan the path from lead to IND-enabling studies, including in vivo pharmacology, pharmacokinetics, toxicology, and the handoff to process development and manufacturing Coordinate antibody production, characterization, and in vitro and in vivo studies with external contract research organizations and academic partners Evaluate AI-designed antibodies, drive them to experimental readout, and feed results back to research teams Ensure experimental data across programs is high quality and well documented, including sequences, protocols, raw data, and failure modes Communicate findings clearly to biology, AI research, and life sciences audiences Minimum qualifications PhD in biochemistry, protein engineering, immunology, molecular biology, or a related field Demonstrated experience in therapeutic antibody discovery and engineering, including at least one antibody you helped take from discovery through candidate selection and IND-enabling studies Working knowledge of what an antibody IND requires across pharmacology, pharmacokinetics, toxicology, and chemistry, manufacturing, and controls (CMC) Comfort navigating ambiguity and defining problems in a rapidly evolving research environment Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills Preferred qualifications 5+ years of therapeutic antibody experience beyond the PhD Track record of advancing more than one antibody program into IND-enabling studies or the clinic, with contributions to pre-IND or IND documents Hands-on experience with antibody expression, purification, and biophysical characterization Experience directing antibody production, assays, and in vivo studies at contract research organizations Structural biology, computational protein design, or coding skills, for example Python for sequence and assay data analysis or structure prediction and protein design tools Experience using AI or ML tools in the life sciences Publications and/or patents demonstrating scientific impact The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: AU: Sydney (45 Clarence St); AU: Melbourne: (260 Burwood Rd); AU: Queensland Remote Worker; AU: New South Wales Remote Worker; AU: Brisbane (243 Edward St); AU: Victoria Remote Worker Workplace: Hybrid The role / impact Reliability is a top strategic priority at Xero, directly influencing customer trust across more than 3,000 services. In this Site Reliability Engineering role, you will help shift reliability into a front-row discipline, moving beyond reactive fixes to uncover and resolve systemic resilience challenges across our global platform. You will partner closely with product teams to design reliability by default, ensuring our systems withstand unexpected events while supporting millions of small businesses. You will take ownership of platform health by building automated tooling, championing chaos engineering experiments, and identifying potential failures before they impact customers. From coordinating incident management rituals and post-incident analysis to introducing load-shedding mechanisms, your contributions will directly safeguard platform availability and elevate engineering practices across the organisation. The team / how they connect You will join a focused Site Reliability Engineering team spanning Australia and the United States, responsible for incident management strategy, artificial intelligence operations tooling, and high-availability frameworks. The team works in close partnership with product and infrastructure squads across Xero, embedding alongside engineers to resolve shared reliability gaps and implement resilient design patterns. Together, the team shares incident commander responsibilities across regions, turning operational learnings into long-term systemic stability. The team is currently working on / Initially, you will focus on - Working across a modern technical stack centred on Kubernetes, AWS (including ECS and managed services), Golang, Python, and C#. - Developing custom Kubernetes operators to automate storage resizing, alert provisioning, and reliability-by-default capabilities for development teams. - Enhancing telemetry pipelines to extract AWS-specific metrics from managed services and route actionable alerts directly to product squads. - Implementing chaos engineering scenarios to test infrastructure failure modes, alongside building API load shedding and rate limiting to protect services against traffic surges. Where and how you can work This role offers the flexibility to work remotely from anywhere in Australia, with office hubs available in Sydney, Melbourne, and Brisbane. Whether you prefer working from home or coming into our collaborative spaces for team gatherings and boost days, we provide the autonomy to create a working routine that suits you best. Here are some of the things we are looking for - You bring a solid background in site reliability engineering or DevOps, with experience diagnosing and strengthening distributed systems. - You have practical experience managing containerised workloads in Kubernetes and running infrastructure on cloud platforms such as AWS. - Your skillset includes practical coding proficiency in Golang, Python, or C#, coupled with curiosity for applying modern AI tools to operational challenges. - You display strong agency and initiative, proactively identifying operational friction and proposing sustainable technical solutions without waiting for instruction. - You demonstrate familiarity with incident management, participating in on-call responses and conducting post-incident reviews that translate into permanent fixes. - You possess clear communication skills, consistently linking technical reliability investments directly to customer needs and measurable business outcomes. Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: Remote Workplace: Remote ABOUT BUFFER We create social media and brand-building software for small businesses, creators, and individuals. Our mission is to provide essential tools to help small businesses get off the ground and grow. Through exceptional customer service and uplifting content, we help our customers believe they can succeed and do good along the way. Buffer is a fully distributed team, and we’ve always aimed to do things a little differently. Since the early days, we’ve focused on building one of the most unique and fulfilling workplaces by rethinking a lot of traditional practices. We also default to transparency, so you can read all about our metrics, and our successes and failures along the way on our Transparency Dashboard https://buffer.com/open. We're united by Buffer's values https://buffer.com/about#values, and we hire and work from all over the world. We strive to create a diverse and inclusive work environment, and we are building a culture where underrepresented groups are welcome and can flourish. Please note that we do travel to work together in person once or twice per year, and those events are highly encouraged to build deeper connections among our small team. As you get to know Buffer and consider joining the journey, you can learn more about Buffer on our Journey https://buffer.com/journey page. Still curious to learn more about the experience on the Buffer team? Feel free to read more from Kirsti https://buffer.com/resources/first-30-days-buffer/ and Sabreen https://buffer.com/resources/joined-3-days-before-the-retreat/ as they share their first experiences with Buffer, as well as from Hailley https://buffer.com/resources/8-years-at-buffer/, who captured why she still calls Buffer home after 8+ years. While unusual at Buffer, we're looking for folks in a specific timezone range. This role is currently open to candidates based between UTC-3 and UTC+3. That gives you overlap with our current security engineer in Sri Lanka and most of our Engineering team, and lets the two of you share incident coverage so neither of you has to work through the night. ABOUT THE ROLE We're hiring a hands-on security engineer to be the tech lead for Buffer's Security team. You'll work alongside Adnan https://www.linkedin.com/in/adnanissadeen/, who has carried security at Buffer for years. Together, you’ll own security and compliance for a 15-year-old profitable company that is rebuilding itself around AI. Two things make this the right moment. Buffer’s product surface is growing: in May, we launched a public GraphQL API with an MCP server and CLI. More than 35,000 organizations have connected an AI tool to Buffer, and we are planning to build a plugin ecosystem on top. Internally, we're becoming an AI-native organization: MCPs on our Claude Team plan, custom connectors, internal tools, and Roo, our own internal agent. We're small and lean, with few processes, and we run on trust around access and permissions. We don't want to lose that, but the surface now grows faster than one person can cover. That means the usual security playbook won't work here. We don't buy enterprise plans for every tool, and we don't make people justify every access request. You’ll make the secure path the easy path to follow. Your role will be to set the direction for security at Buffer and to do much of the work yourself. You'll decide which open security problems to address first, write code to fix some of them, and lead incidents when they happen. We're looking for an enabler and a team player, not a gatekeeper. This is a generalist role by design. WHO YOU’LL WORK WITH You’ll report to Miguel, https://www.linkedin.com/in/migueldavid/ Engineering Manager for the Infrastructure and Security teams. Day-to-day, the Security team is you, Adnan, and Miguel. Adnan knows how everything at Buffer fits together and where the sharp edges are. Together, you’ll own planned security work as well as the work that keeps the lights on: the security inbox, requests from other teams, maintenance, and chores. You’ll lead the team’s direction and standards. You will also work closely with product engineering teams to ensure that what we build meets a strong security bar. That means collaborating on tech spec reviews and growing the group of security champions across the teams. Your peers from our Advocacy (customer support) and People teams will rely on you to support them with security and compliance needs that come up in their work, from customer security questions to vendor reviews and policy. WHAT YOU’LL BE WORKING ON - 🧭 Lead security at Buffer. Define the strategy and roadmap, set priorities, drive execution, and change how we work where it matters. If you see a problem outside your lane, say so and drive the fix. - 🧰 Build. Identify the problem, define the solution, then build it with Adnan: tooling, automation, processes. - 🔁 Put security in the development loop. Check on every PR, threat modeling in tech specs, dependency, secrets, and supply chain hygiene, and review steps that hold up as more of our code is written with AI agents. - 🔐 Advance operational security. Secure our day-to-day operations to meet industry-wide standards while maintaining the flexibility afforded by Buffer’s high-trust environment. - 💡 Keep the lights on. Security inbox, requests from other teams, maintenance and chores, shared with Adnan. Much of this is manual today, and we’d love you to automate what you can. - 🚨 Lead incidents and take part in our engineering-wide on-call rotation. Set the standard for how we run a security incident, then hold the team to it. Run tabletops with the rest of Engineering, and ensure the gaps are fixed. - 🤖 Secure the AI surface. Threat-model what we’re building, from agents with tool access to connectors and in-product AI, and set guardrails so Buffer can move fast on AI without guessing. - 🐛 Run vulnerability disclosure. Triage reports from outside researchers, fix or route the real ones, and decide how the program grows. - 🤝 Own compliance and customer trust. SOC 2 and Meta platform compliance are the big ones today. We want them to make Buffer safer, not only to pass audits, but also to automate evidence where you can. Security questionnaires reach us through Advocacy. Help answer them, and build what lets customers find answers on their own (a Trust Center, for example). HELPFUL SKILLS AND EXPERIENCE - You’ve been the senior security person somewhere without a CISO above you. You know what it means to set direction without a mandate and earn it through work. - You have hands-on application and API security depth in a multi-tenant SaaS, ideally one with a public API: authorization models, OAuth and OIDC, session and auth flows, IDOR and SSRF, and threat modeling. You've found these bugs and fixed them, not only reported them. - You write code. You can read and change a TypeScript codebase well enough to ship a fix and review someone else’s (legacy PHP and Python show up more rarely, too). - You’ve led security incidents end-to-end, including the writing of status updates, customer comms, and postmortems that people act on. - You’ve worked with AWS, Kubernetes, and Cloudflare, or similar, enough to reason about infrastructure risk with an infrastructure team. You don’t need to run it. - You’ve run a SOC 2 or similar program, or worked closely with one, and you’d rather automate evidence collection than do it by hand. - You've run or triaged a vulnerability disclosure or bug bounty program, and you can tell a real report from noise quickly. - You have strong opinions, and you can hold them loosely. You are comfortable disagreeing with a senior engineer’s design, and working together to find the best solution (sometimes changing your mind when their argument is better). - You’re fluent with modern AI tools, and you use them to multiply your output and your team’s. You’ve thought hard about securing systems that use them. - You thrive in remote, async environments, and you follow through. You're clear in your thinking and generous with context, and you close the loop on what you commit to. Most of your influence here will be written. - Bonus points if you’re already a Buffer user or familiar with social media management tools. OUR TECH STACK - Product. Node.js (TypeScript) across most services in a monorepo, backed by MongoDB; a REST API and PHP being retired for legacy services. iOS and Android apps. A public GraphQL API, MCP server, CLI, and connectors. - Infrastructure. AWS (EKS, IAM, SQS, S3, CloudFront), Terraform, ArgoCD, GitHub Actions, Cloudflare (WAF, Zero Trust, Workers, DNS). - Security and compliance. Vanta for SOC 2, Dependabot, gitleaks, AWS GuardDuty, Cloudflare WAF and Zero Trust, Action1 for device management, 1Password, and Google Workspace as the identity layer. - Observability and incidents. Datadog, Sentry, incident.io http://incident.io, and PagerDuty. - AI. Claude Team across the company, internal agents and MCP servers built in-house, in-product AI features. APPLY FOR THE JOB Do you believe you're a fit for this role and want to join the Buffer team? We'd love to hear about you! Here's what our hiring process looks like: 1. Application. A short form with your CV, LinkedIn, a few yes/no questions, and an example of your writing. 2. Questionnaire. If there’s a match, we’ll email you a short set of questions to learn a bit more about you! 3. Interview process: Meet with several teammates across a few Zoom calls, starting with Miguel https://www.linkedin.com/in/migueldavid/, Engineering Manager for Infrastructure and Security, and the hiring manager for this role, and then a handful of other Buffer teammates and peers. 4. Take-home exercise. During our interview process, we'll ask you to do an asynchronous task so we can see your work in practice and discuss it live. 5. Meet the CEO. Get to know Joel https://www.linkedin.com/in/joelgascoigne/, our Founder CEO. 6. Collaboration period. Two paid days working with the team on a real project, so that we can each see what it's like to work together. PRIVACY POLICY By submitting the application, you consent to Buffer collecting and processing your personal data for recruiting purposes. Find more details in our Privacy Policy https://buffer.notion.site/Privacy-Policy-for-Applicants-230a7f5a00fd80e48478f09171d18a24?pvs=143.

Location: Remote About HumanSignal Real-world data is the competitive edge in AI. HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out. If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk. About the Role Services Support Specialists are the dedicated, global point of contact for HumanSignal's contractor population — a workforce-operations function distinct from Enterprise Support. Where Enterprise Support is primarily technical and customer-facing, this role resolves payment, identity/verification, account-access, onboarding, and project-related questions for contractors working across every timezone. Key Responsibilities Own and resolve inbound contractor tickets in Zendesk, including payment/payout issues, identity and KYC verification, account access, and onboarding or assessment blockers. Serve as a contractor's single point of contact, coordinating across teams rather than leaving them to navigate multiple channels on their own. Escalate issues outside Services Support's scope to the appropriate team: Payments/Finance, Verification/Trust, Project Operations, Support Engineering/Engineering, or Safety/Security. Monitor and handle annotator requests within Discord, escalating to the appropriate delivery team resource when needed. Apply P0-P3 severity classification to incoming tickets and follow the corresponding response process. Identify and flag repetitive, low-complexity ticket types (roughly 81% of tickets require two or fewer agent comments) for deterministic self-service or automation. Participate in a quarterly review of ticket volume and coverage against the schedule below. On-Call Responsibilities Acknowledge P0 pages within approximately 15 minutes; unacknowledged pages automatically escalate to that week's secondary on-call responder. On-call is reserved for Critical issues only — for example, a systemic inability to work, widespread payment or verification failures, major production incidents, or credible safety/security concerns. Routine P1-P3 tickets remain queued for the next scheduled shift. Qualifications Experience in a support or operations role, ideally supporting a global or contractor/gig workforce. Comfort working across payment, identity/verification, and account-access issues, with the judgment to know when to resolve directly versus escalate. Clear, professional written communication suited to a global contractor population. Willingness to participate in the rotating P0 on-call schedule. Working proficiency with Zendesk (or a comparable ticketing platform) and Discord. Ability to work independently during off-hours coverage while following documented escalation paths. What Success Looks Like SLA attainment on first response and time-to-resolution, against an initial planning estimate of approximately 15-30 minutes of direct handling time per ticket. P0 pages acknowledged within the target window, with escalations to the secondary responder tracked and rare. Low rate of tickets requiring re-escalation or reopening. Contractors get a single, clear path to resolution rather than moving unassisted between Support, Project teams, Payments, and Verification. A growing share of high-volume, low-complexity ticket types shifted to self-service or automation. At HumanSignal we pay based on regional compensation market rate ranges across the globe. We are hiring for this role across North America. The base cash compensation range for the United States is $55,000 to $70,000 USD. These ranges are provided by market data and are in good faith. The final offer details are determined by several factors including candidate experience, expertise, as well as applicable industry knowledge and may vary from the pay ranges listed above.

Location: Santa Barbara, United States; Waltham, United States 📍 Location: Santa Barbara, CA / Waltham, MA 📄 Employment Type: Contract-to-Perm 🏢 Work Arrangement: To Be Confirmed 🚀 Start Date: ASAP 💰 Compensation: TBD — Based on skills and experience About the Role We’re seeking an experienced EEE Parts Engineer to support aerospace and defense hardware programs. This role focuses on electrical, electronic, and electromechanical (EEE) component selection, qualification, screening, reliability, and lifecycle management to ensure mission-critical hardware meets program requirements. You’ll collaborate with Electrical Engineering, Quality Engineering, Supply Chain, and Program Management teams to maintain approved parts lists, evaluate suppliers, manage component obsolescence, review qualification data, and support failure investigations. What We're Looking For We’re looking for a detail-oriented engineer with strong knowledge of EEE component reliability, qualification, and screening requirements. The ideal candidate can assess component risks, maintain technical documentation, and work across engineering and supply-chain teams to support reliable aerospace and defense hardware. Key Responsibilities Parts Selection and Documentation Develop and maintain parts selection and screening plans, including acceptable component classes and qualification requirements. Build and maintain master parts lists and approved or preferred parts lists. Track manufacturer information, part numbers, screening levels, qualification status, and approved alternatives. Monitor component obsolescence and lifecycle status. Requirements and Supplier Management Review statements of work, technical specifications, and contractual documents to identify EEE parts requirements. Communicate applicable requirements to design teams and suppliers. Evaluate component manufacturers and distributors based on quality, reliability, and supply-chain integrity. Help ensure authorized distribution practices and appropriate anti-counterfeiting controls. Identify viable alternative components when necessary. Qualification and Technical Reviews Prepare technical data packages for nonstandard part approvals, including qualification data, manufacturer reliability information, and process-change evaluations. Present and defend proposed components to internal or customer Parts Control Boards. Review component test data and qualification reports against program requirements. Support Destructive Physical Analysis (DPA) lot-sample teardowns. Review and support Prohibited/Restricted Materials Analysis (PMA) dispositions. Failure Analysis and Obsolescence Support investigations involving EEE parts that fail incoming screening, board-level testing, or system-level testing. Coordinate with failure analysis laboratories to identify root causes and support corrective actions. Monitor industry alerts and advisories, including the Government-Industry Data Exchange Program (GIDEP). Assess the impact of alerts on existing designs, inventory, and ongoing procurement activities. Recommend appropriate dispositions and mitigation strategies. Cost and Schedule Support Estimate and track costs and schedules associated with parts screening, qualification, and procurement. Provide EEE parts-related cost, risk, and schedule inputs for proposals and program planning. Required Qualifications Bachelor's degree in Electrical Engineering or a related technical field with approximately 5 years of applicable industry experience , or a master's degree with approximately 3 years of experience . Strong working knowledge of EEE components, including hermetic and plastic-encapsulated devices. Familiarity with applicable industry standards and military specifications, including: MIL-STD-883 MIL-STD-750 MIL-PRF-38534 MIL-PRF-38535 MIL-PRF-19500 Experience with or working knowledge of Destructive Physical Analysis under MIL-STD-1580. Ability to prepare clear technical reports and communicate findings to engineering teams, management, and customers. Ability to collaborate effectively with Electrical Engineering, Quality Engineering, Supply Chain, and Program Management. Availability to begin promptly and commit to the expected contract period. Export Control and Clearance U.S. Person status is typically required for positions involving access to export-controlled data. Eligibility to obtain and maintain a security clearance may also be required, depending on program requirements. Preferred Qualifications Familiarity with additional military specifications: MIL-PRF-55681 MIL-PRF-55342 MIL-PRF-55310 Experience monitoring and dispositioning GIDEP alerts and advisories. Experience performing or reviewing Prohibited/Restricted Materials Analysis, including tin-whisker and wire-bond material risk assessments. Experience supporting EEE parts qualification for space, launch vehicle, or other harsh-environment defense programs. Experience preparing technical data packages for or presenting to Parts Control Boards. Experience supporting Material Review Board (MRB) dispositions for nonconforming parts and materials. Previous experience in contract or consulting roles within aerospace and defense environments.

Location: Remote, Canada GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. About the role As an Intermediate Backend Engineer, you will take backend features and improvements from clarifying the problem through shipping them and following up in production. You will work within a product area, partnering with Product Management, Frontend, Infrastructure, and Security to deliver predictably and contribute to the quality, security, performance, and maintainability of shared backend code and services. You will be trusted to work with minimal guidance, to know when to seek help, and to communicate clearly in a remote, asynchronous environment — with other tenured engineers alongside you to review your work, think through hard problems with you, and help you grow. Why you’ll love this role Ownership: You'll take features from requirements through delivery and follow-up; your code will run on a platform used by millions of users. Learning and Growth : You’ll work alongside your engineering team, who treat code review and design review as a learning loop rather than a gate — one of the fastest ways to grow your engineering judgment. Innovative Culture: You’ll use AI as a genuine part of daily engineering work, developing the judgment to know when to trust it and when not to. Autonomy: You’ll thrive in our remote-first, asynchronous organization, where clear written communication and self-direction are the pillars of success. User-Centric Collaboration: You’ll partner closely with PMs and designers to shape requirements, so you understand why you’re building something, not just what. What you’ll do Own and Ship Features: Design, implement, test, and ship backend features and improvements with minimal guidance, working in Ruby/Rails, Go, or any other modern languages. Build for Production: Write maintainable, secure, observable, and performant code. Design and maintain APIs, background jobs, integrations, and bounded service functionality, and work with data models, migrations, indexes, and query behavior. Test and Review: Add and improve automated coverage — unit, integration, contract, and end-to-end where appropriate — and review others’ code for correctness, maintainability, security, performance, and operational risk. Operate What You Build: Investigate build, test, deployment, and runtime failures at the feature boundary, identify technical debt and propose practical improvements, and take part in on-call or operational support where your team’s ownership model requires it. Leverage AI: Use AI productively in daily work, validate what it produces, and understand where its limitations matter. On Call Support: Take part in on-call or operational support where your team’s ownership model requires it. What you’ll bring Backend Fundamentals: Professional experience building and shipping production backend applications, with strong programming, API, database, testing, debugging, and performance fundamentals. Adaptability: Experience with Ruby/Rails, Go, or any other modern backend language. We value the ability to learn and adapt over mastery of a single language. Feature Ownership: The ability to take a feature from clarification through delivery and follow-up, working independently while seeking input at the right time. Practical Judgment: Sound instincts about security, reliability, performance, maintainability, and operational risk, plus an understanding of modular backend boundaries and the consequences of coupling. Clear Communication: Strong written communication and effective collaboration in a remote, asynchronous environment. AI Fluency: Practical experience with AI coding tools, including the ability to review and correct what they generate. Helpful experience Production Go services, APIs, concurrency, profiling, or gRPC. Docker, Kubernetes, Helm, CI/CD, or cloud deployment. Rust, particularly for systems, security, performance, or platform work. PostgreSQL, schema evolution, caching, queues, messaging, or event-driven workflows. Observability using metrics, logs, traces, dashboards, and alerts. Contributing to a modular monolith, bounded context, shared component, or independently operated service. Remote-Global How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Waltham, United States; Santa Barbara, United States ABOUT THE JOB We are looking for an experienced EEE Parts Engineer to join us on a contract basis, owning parts engineering across one or more hardware programs for the duration of the engagement. In this role, you will work with Electrical Engineers to select and qualify parts for new designs, with Quality Engineers to define screening, inspection, and test requirements, and with Supply Chain to select and monitor part suppliers. You will build and maintain parts lists and screening plans, review contractual and customer requirements for parts impacts, shepherd nonstandard parts through internal and customer approval processes, and support root-cause investigations when parts fail during test. This role requires both deep technical knowledge of EEE parts and the collaboration skills to work effectively across engineering, quality, and program disciplines. This is a contract position with a defined period of performance. Contract duration and any extension options will be discussed during the hiring process. WHAT YOU'LL DO • Parts Selection & Screening Plans: Develop and maintain the program's parts selection and screening plan, defining acceptable part classes, screening levels, and qualification requirements for EEE parts used in the design. • Parts List & Baseline Management: Build and maintain a master parts list (preferred/approved parts list) tracking manufacturer, part number, screening level, qualification status, and approved alternates for every part used, including obsolescence and lifecycle tracking. • Requirements Flow-down: Review statements of work, specifications, and contractual documents to identify EEE parts requirements, and flow those requirements down to design teams and suppliers alongside viable alternative part solutions. • Supply Source Selection: Support evaluation of component manufacturers and distributors for quality, reliability, and supply-chain integrity, including authorized distribution and anti-counterfeiting controls. • Nonstandard Part Approval: Prepare and submit nonstandard part approval data packages (qualification data, manufacturer reliability data, process-change evaluations), and present/defend them to an internal or customer parts control board. • Part Qualification & Test Data Review: Review incoming part test data and qualification reports against program requirements, including oversight of Destructive Physical Analysis (DPA) lot-sample teardowns and Prohibited/Restricted Materials Analysis (PMA) dispositions. • Failure Analysis & Corrective Action: Support investigation of EEE parts that fail incoming screening, board-level test, or system-level test; interface with failure analysis labs to determine root cause and drive corrective action. • Obsolescence & Advisory Monitoring: Monitor industry alert/advisory systems (e.g., GIDEP) for notices affecting parts used on the program, and assess and disposition the impact on existing designs, inventory, and in-process procurements. • Cost & Schedule Support: Estimate and track the cost and schedule impact of parts screening, qualification, and procurement activities, and support proposal efforts with EEE parts cost, risk, and schedule inputs. REQUIRED QUALIFICATIONS • Education: Bachelor's degree in Electrical Engineering or a related technical field, with approximately 5 years of applicable industry experience (or a Master's degree with approximately 3 years). • EEE Parts Knowledge: Strong working knowledge of EEE parts, including hermetic devices and plastic encapsulated devices, and the industry standards and military specifications that govern them. • Screening & Qualification Standards: Familiarity with MIL-STD-883 and MIL-STD-750 (test methods) and MIL-PRF-38534/-38535/-19500 (hybrid, integrated circuit, and semiconductor device specifications). • DPA & Failure Analysis: Experience with or working knowledge of Destructive Physical Analysis (MIL-STD-1580) and interfacing with part failure analysis labs to support root-cause investigations. • Communication: Ability to produce clear, concise written and verbal technical reports for engineering teams, management, and customers. • Cross-Functional Collaboration: Demonstrated ability to work effectively across Electrical Engineering, Quality Engineering, Supply Chain, and Program Management. • Availability: Ability to begin the contract engagement promptly and commit to the expected period of performance. • Export Control: U.S. Person status is typically required for roles accessing export-controlled data; eligibility to obtain and maintain a security clearance may also be required depending on program. PREFERRED QUALIFICATIONS • Familiarity with MIL-PRF-55681, MIL-PRF-55342, and MIL-PRF-55310 (chip capacitor and resistor specifications). • Experience monitoring and dispositioning GIDEP (Government-Industry Data Exchange Program) alerts and advisories. • Experience performing or reviewing Prohibited/Restricted Materials Analysis (PMA), including tin-whisker and wire-bond material risk assessment. • Experience supporting part qualification for space, launch vehicle, or other harsh-environment defense programs. • Experience preparing data packages for, or presenting to, an internal or customer parts control board. • Experience supporting Material Review Board (MRB) disposition of nonconforming parts and materials. • Prior experience working in a contract or consulting capacity within aerospace and defense environments. Salary: $75 – $80 / hour

Location: US Remote Workplace: Remote SR. MANAGER, CREDENTIALING OPERATIONS US Remote · Full-time ABOUT FINNI HEALTH Finni Health empowers autism care providers to start, run, and grow their own practices. We democratize autism care by providing access to our insurance network, purpose-built EHR software, HR solutions, and clinical support. We've experienced rapid growth and are backed by top-tier investors like General Catalyst and YCombinator. We seek smart, driven individuals eager to innovate in a dynamic, fast-paced environment. WHAT YOU WILL BE DOING: As Sr. Manager, Credentialing Operations, you will own the function that determines how fast a Finni practice can start seeing clients and getting paid. A provider who is not enrolled with a payer cannot be billed for, so credentialing sits in front of our revenue and in front of families waiting for care. You will lead a team of twenty: four Credentialing Managers and sixteen coordinators and associates working offshore across time zones. Each manager owns one stage of the credentialing lifecycle. Onboarding & Submission runs from offer signed to first payer submission. Follow Up & Resolution runs from submitted to enrolled, and is not finished until proof of participation is attached. Provider Maintenance owns the provider record after enrollment, including licenses, expirations, re-attestation and roster accuracy. Enrollment Integrity owns accuracy across all three. Each stage carries its own measure. This is a build job as much as a leadership job. Too much of how this function works today lives in a few people's heads, our reports do not always agree with each other, and the controls that should make it safe when someone is out are not all in place. You are here to run it and to make it durable. - Team Leadership: Hire, develop and set the performance bar across managers and coordinators. Build the bench this function has not had. - Completing the Reorganization: The function is moving from managers aligned to groups of practices to managers who each own one stage of the lifecycle. That transition is in flight and you will finish it. The hard part is not the org chart, it is keeping the state and payer knowledge that currently lives with a group-aligned manager while the work is re-cut around stages. - Time to Enrolled: Own the number, meaning the days from a provider signing their offer to being enrolled with a given payer. Underneath it: blocked billing by cause, clean submission rate, aging and follow-up compliance. You own whether the number is right, not just whether the dashboard renders. - Reporting We Can Trust: Reconcile the places our systems disagree about the state of an enrollment, and keep them reconciled. - Controls and Coverage: Remove the single points of failure. The review queues, the payer configuration that governs who may bill, and the approvals that keep an unenrolled provider off a schedule should never depend on one person being at their desk. Build the cross-training, segregation of duties, and second set of eyes that make that true. - Data-Handling and Payer Restrictions: A growing list of payers and state Medicaid programs prohibits offshore handling of protected health information. You will own the restricted-payer list, enforce it in how work is actually assigned rather than in policy alone, and tell us when the only answer is an onshore hire. - Process and Documentation: Build the per-payer requirements library so a submission goes out as soon as that payer's minimum is met instead of waiting on the strictest payer on the list, plus written procedures by state and payer specific enough that a coordinator who has never worked a given state can submit there. - Backlog Programs: Enrollment records without documented proof of network participation, enrollments still open on providers who have left, records with no approval date. Scope each one, run it to completion, and prevent it from recurring. - Payer Relationships and Compliance: Provider-level revalidations, roster management, directory accuracy, demographic updates, and the judgment that comes with them. When a payer offers something like provisional credentialing, you weigh the risk and make the recommendation. - Product Partnership: Be the credentialing voice in Product. Translate what the team needs into requirements engineering can build, and verify the build solved the problem before it is called done. Our enrollment systems are mid-migration and there is real work here. - Cross-Functional Collaboration: Work closely with Practice Success, revenue cycle, payer contracting, HR and compliance. - Additional Responsibilities: Adapt and take on evolving responsibilities as Finni Health grows and the regulatory landscape changes. ABOUT YOU: You have run a credentialing function, not just worked inside one, and you are as comfortable rebuilding a process as you are working an escalation. - Experience: 5+ years in provider credentialing or payer enrollment, multi-state, across commercial payers and Medicaid or Medicaid managed care. Medicaid experience is required. Hands-on with CAQH, NPPES, PECOS, state Medicaid portals and commercial payer portals. You have submitted applications yourself and you know where they stall. - People Leadership: 2+ years managing and developing a team, ideally including leads or managers rather than only individual contributors. Be ready to tell us about someone you developed and someone you had to move on from. - Reorganizing a Team: You have changed how a team is structured, not just who is on it. Moving people from one way of dividing the work to another, keeping the knowledge that lived in the old structure, and holding the change in place after the announcement. - Process Building: Demonstrated expertise in identifying inefficiencies and building the fix, not only naming it. SOPs that got used, a workflow you designed, an SLA you set and then held a team to. - Analytical and Problem-Solving: Strong ability to work with operational data, identify trends and root causes, and implement data-driven solutions. You can define a metric, notice when a number looks wrong, and go find out why. - Compliance Judgment: You understand that credentialing is a control function. Delegated credentialing, NCQA standards, payer audits and data-handling restrictions are familiar territory, and you treat a bypassed guardrail as a serious finding rather than a convenience. - Offshore Teams: Experience leading or working closely with offshore teams, and an honest view of what works and what does not. - Communication and Collaboration: Excellent written and verbal communication, with proven ability to work across internal teams and with external stakeholders including payers. Much of what this role produces is written. - Tech Proficiency: Proficient in Google Suite, Slack, and credentialing platforms such as Verifiable, Medallion, Modio, Symplr or CAQH ProView, with an opinion about what these tools do and do not do well. Experience writing requirements for a product or engineering team is a plus. - Mission Alignment: Passion for Finni's mission to democratize autism care and empower providers to run strong, compliant practices. - Adaptability and Agility: Comfortable thriving in a dynamic, fast-paced startup environment, embracing change, and navigating ambiguity with a proactive mindset. WHAT SUCCESS LOOKS LIKE - First 30 days: You know the payer landscape we operate in, you have met every manager and coordinator, and you can tell us where the days actually go between offer signed and enrolled. - First 60 days: Time to Enrolled is reported weekly and we trust the number. Blocked billing is on a dashboard with a cause and an owner against every line. No step in the function depends on a single person being available, and you can show us the coverage plan. - First 90 days: Blocked billing from enrollment is measurably down and the trend has turned. The per-payer requirement library covers our top payers by volume. A new coordinator can be trained from written material instead of by shadowing. - First 6 months: The stage-based structure is fully in place and the state and payer expertise survived the move. The manager layer is stable and developing, and you are telling us what credentialing should look like two years out rather than reacting to what it looks like today. WHAT THIS ROLE IS NOT You do not own payer contracting or payer sales. Negotiating and signing payer agreements is a separate function with its own leader, and you own getting providers enrolled under the agreements we have. Group and facility-level enrollment, organization revalidations and single case agreements sit with that same function, so your scope is the provider rather than the organization. You do not own claims or collections either. Revenue cycle owns a claim once it is clean, and you own whether the provider was enrolled so the claim could go out at all. BENEFITS - 401(k) - Health insurance - Dental insurance - Vision insurance - Flexible schedule - Paid time off - Paid Holidays Ready to make a significant impact at a rapidly growing healthcare startup? We'd love to hear from you!

Location: Palo Alto, California, United States; San Francisco, California, United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Role Overview: Every project we run starts with people: software engineers, PhDs, physicians, lawyers, linguists, designers and other experts whose work trains and evaluates our customers' AI models. When a project needs 20 or 500 of them, the request comes to our Talent Matching team. We commit to a hiring timeline, find and assess the talent, and get them working by the date we promised. The Marketplace Operations Lead takes on the hardest of those requests: US-based roles, role types we've never hired for before, and large, urgent hiring pushes where a delay is visible to the customer. When a project is falling behind, you'll be the first person we call. You'll pull in our sourcing, assessment, talent operations and onboarding teams to get it back on track, and you'll stay on it until the talent is working. This is a senior individual-contributor role with a lot of room to grow. You'll work from our San Francisco or Palo Alto office, partner closely with matching teams in other time zones, and help set the standard for how the whole team plans, communicates and escalates. As the matching organization grows, we expect this role to grow with it. Key Responsibilities: Hiring requests and timelines Pick up new hiring requests the same day they come in. Work through the requirements with the project team, flag risks early, and commit to a hiring timeline you can stand behind: how many people by which date, and what you need from the project team to get there. Be the single point of contact for the project team, and know the status of every open position without having to ask anyone. Decide how each kind of candidate should be assessed, and design the screening with the project team so it protects quality without adding days to the process. At-risk hiring and escalations Raise a flag the moment a hiring timeline is at risk, and bring a plan to recover it. Use every option available: adjust requirements with the project team, open new sourcing channels, bring in staffing partners, adjust pay rates within approved limits, and step in on screening, scheduling or candidate calls when something stalls. Be the person project leaders escalate to and trust to fix it, including outside normal hours when a large hiring push needs it. US and specialized talent Own hiring for US-based roles end to end, from sourcing strategy through assessment to start date. Take on new and unusual role types, and turn each one into a playbook the rest of the team can reuse. Metrics, tools and the team Know your numbers cold: time to first hire, hires against the committed timeline, quality after start, and how many positions are at risk and for how long. Report them in a short, standard format leadership can read in a minute. Work hands-on with our product and engineering teams on our matching platform, AI interviewer and assessment tools. Use them every day and send back specific feedback on what's slowing you down. Raise the bar for the team around you through clear process, sharp written updates and coaching in the moment. Basic Qualifications: 5+ years in fast-moving operations roles, such as marketplace or supply operations, strategy and operations, consulting, early-stage startup operations or staffing. A track record of taking something that was off track and getting it delivered on a hard deadline, including the parts that weren't your job. A steep learning curve. You get up to speed on an unfamiliar domain quickly enough to judge what good looks like, whether that's a software engineer, a physician or a linguist. Excellent communication, written and in person. You give senior stakeholders and customers a clear picture in a few lines, especially when the news is bad. You work well with product and engineering. You adopt tools that are still being built, find what's broken, and turn it into specific, useful feedback. Comfort with data. You build your own reports in spreadsheets or SQL, and you manage your work from the numbers. High hustle and high ownership. When a step owned by someone else stalls, you step in and do it. Based in the San Francisco Bay Area and able to work from our San Francisco or Palo Alto office Preferred Qualifications Experience in a two-sided marketplace, or at an AI data, annotation or expert-network company. Experience running a supply or hiring funnel at volume (sourcing, screening, onboarding). Experience leading or mentoring a team. Experience working with distributed teams across the Americas, Europe and India. Hands-on use of AI tools in your own work. How we work One owner per position. The person who owns the position owns the outcome, even when other teams do part of the work. Speed matters. We measure ourselves in days, and we're working toward hours. Flag problems early, with a plan. The only failure we don't accept is a surprise. Low ego. The outcome matters more than who gets the credit. Compensation and logistics $150,000 – $230,000 + equity Onsite in San Francisco or Palo Alto, with occasional travel. Reports to the Head of Platform Operations. #LI-VC1 Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Senior Engineer on the Life Sciences team, you'll build biology software that our own scientists and the wider research community can depend on, and you'll be one of the main people representing that work to computational biologists outside Anthropic. The Life Sciences team works to accelerate progress in biology with AI, combining frontier models with hands-on computational and experimental research. We want the tools, pipelines, datasets, and benchmarks we build in genomics and structural biology to be useful beyond our own projects, so we plan to release them to the community. Computational biology has a long tradition of open, shared software, and we want to contribute to it well. Every release should be something a researcher can install, run on their own data, and trust: correct on real inputs, validated against reference data and established methods, documented, versioned, and maintained after launch. You'll own that standard. You'll write a large share of the code yourself, decide when something is ready to ship, and stay with it once people start using it. You'll also be an active member of the biology software community: maintaining public repositories, answering issues, speaking at conferences and workshops, and bringing what you hear from researchers back into what we build next. We use Claude and AI coding agents heavily to build software, and we expect you to do the same across design, implementation, testing, and review. Code written by an agent is held to the same standard as code written by hand: you should understand it, test it, and measure its performance before it ships. We're looking for someone with deep software engineering experience who already works this way. The shape of the role is flexible. You might spend most of your time as an individual contributor, or you might lead a small group of engineers and scientists while continuing to contribute directly. Your focus can be genomics, structural biology, or both. Experience in other areas of computational biology is welcome, and we expect the work to range more widely over time. What matters most is a record of biology software that other people have adopted and relied on. This is a chance to shape how AI is put to work in biological research, on problems that matter for human health and scientific understanding. If building software that scientists trust is the work you want to do, we want to hear from you. Key responsibilities Design, build, and maintain biology software in genomics and structural biology (libraries, command-line tools, pipelines, datasets, and benchmarks) for use by researchers and AI agents, inside Anthropic and externally Own the path from research code to public release, including testing, validation against reference data and established tools, benchmarking, documentation, and packaging, and make the call on when something is ready to ship Maintain what we release: triage issues, review outside contributions, and manage breaking changes Represent the team in the biology community through conferences, workshops, tutorials, and direct work with researchers and maintainers, and turn what you learn about their needs into priorities for the team Partner with the team's computational and experimental scientists to turn research code into well-tested, reusable software Lead the technical direction of the projects you own through design review, code review, and mentoring, and, depending on your interests and the team's needs, lead a small team Build with Claude and AI coding agents as your default way of working, hold agent-written code to the same standard as your own, and set the team's practices for reviewing and validating it Minimum qualifications Have built, released, and maintained biology software that researchers outside your own group use, with evidence of adoption you can point to (for example public repositories, package downloads, citations, or use in other groups' pipelines) Have deep working expertise in genomics or structural biology, including the data types, file formats, standard tools, and common failure modes of at least one of these fields Are proficient in Python and comfortable working with large datasets in Linux and cloud or cluster computing environments Practice rigorous testing and release engineering: unit and integration tests, continuous integration, validation against reference data, packaging, and versioning Use AI coding tools as a central part of how you build software, and can show how you verify the correctness and performance of code you did not write by hand Have led a technical project with multiple contributors, setting direction and reviewing others' work while continuing to write code yourself Can explain technical work clearly to both biologists and engineers, in writing (documentation, tutorials) and in person (talks, workshops) Preferred qualifications Depth in both genomics and structural biology A record as the creator or a core maintainer of a widely used open-source tool in computational biology Experience managing or formally leading a team of engineers or scientists A graduate degree in computational biology, bioinformatics, computer science, or a related field, or equivalent experience Proficiency in a systems language such as Rust, C++, or C, and experience with performance work on large biological datasets Experience building software in other areas of computational biology, such as phylogenetics, proteomics, cheminformatics, or high-throughput screen analysis Experience shipping software built largely with AI coding agents, building agentic systems on large language models, or training machine learning models on biological sequence or structure data The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote - Colombia About Backblaze Backblaze is the object storage leader in the open cloud movement, fueling customer success with cloud storage built purposefully to unlock budgets, unburden administrators, and unleash innovators. Together with our partners, we’re helping customers break free from the restrictive, overpriced legacy solutions that hold them back, and blaze forward with the full power of the open cloud in their hands. Founded in 2007, we scaled the business with less than $3 million in outside funding until 2021, when we did a traditional IPO on the Nasdaq stock exchange. Today, Backblaze generates over $100m in revenue and is the leading specialized storage cloud - managing over three billion gigabytes of data storage for 500K+ customers in 175+ countries, including businesses, developers, IT professionals, and individuals. Want to know what you’ll be doing? You will work on our data infrastructure platform which supports the B2 Object Storage and Computer Backup products, responsible for the data infrastructure that everything runs on. You will help improve automation, observability and stability for durability, increase throughput, and drive architectural changes to support the long term requirements of our service. Responsibilities: Design and build automation frameworks that let other engineers provision, configure, and repair fleet infrastructure themselves Design and extend the observability stack (metrics, logs, traces, alerts) that tells us whether the storage platform is healthy and where it is degrading Build reporting, dashboards, and visualizations that give engineering and leadership a clear view into fleet health, capacity, and operational trends Build system health tooling that detects failing hardware, drifting configuration, and capacity risk before they turn into incidents Lead technical design discussions and produce clear design documents for changes that span multiple services and teams Drive the implementation of large features from design through rollout, including the migration and backfill work that real systems require Partner with the on-call rotation to turn recurring toil and incident findings into automation and better signal The Right Fit: 7+ years of backend development in an enterprise environment, working in an object-oriented or systems language (Java, Rust, C++, C#, Go, or similar) Experience designing automation frameworks or platforms that other engineers build on Experience building large scale software systems running on thousands of servers Experience building automation or tooling that other engineers depend on daily, whether internal platform services, operational tooling, or a deployment and configuration pipeline Working knowledge of an observability stack (Prometheus, Grafana, OpenTelemetry, ELK, Datadog, or equivalent), including instrumenting a service and designing alerts people trust Strong Linux fundamentals and comfort operating in a bare-metal or hybrid environment rather than a fully managed cloud Professional experience incorporating AI-assisted development tools (Gemini, Cursor, Claude Code, or similar) Comfortable with all aspects of the software development lifecycle, including design, implementation, testing, and rollout Exhibits curiosity and seeks to understand before offering solutions Communicates proactively in a remote environment by keeping the team informed, surfacing blockers early, and moving work forward Applies analytical thinking to ambiguous problems Bonus points for: Proficiency in Java Experience with configuration management or infrastructure-as-code tooling (Ansible, Salt, Puppet, Chef, Terraform) Experience designing SLOs and error budgets, or reducing alert noise on a fleet running at scale Experience with time-series databases and query languages such as PromQL Experience automating hardware lifecycle work: burn-in, failure detection, drive replacement, decommissioning Experience with discovering and implementing performance improvements, including CPU and IO Understanding of Linux internals and file systems Familiarity with hard drive performance and optimization, including host-managed SMR Experience building and interpreting models, dashboards, or reports At this point, we hope you're feeling excited about the job description you're reading. Learning, developing, and growing are key parts of our culture, so even if you don't meet every requirement, we still encourage you to apply. At Backblaze, we value being fair and good to our customers, partners, and employees. That’s why diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We believe that our dedication to cultivating a diverse workspace not only allows us to better serve our customers in over 175 countries but further reinforces our commitment to doing the right thing. We are proud to be an Equal Opportunity Employer. To understand more about the data we collect and process as part of your application, please view our Backblaze Employee Privacy Notice.

Location: Europe; Canada Workplace: hybrid ABOUT YOU We are looking for a Senior QA Engineer who has tested real on-chain products — the contracts and the transactions, not only the web app in front of them. You will own quality for Xsolla's smart wallet on Xsolla ZK, our Ethereum-compatible ZK rollup: the wallet players use to hold, receive and send tokens and in-game items, signing in with the account they already have. The work runs on both sides of the chain. On the backend, you will confirm that a wallet address pre-computed from a salt is the address that actually gets deployed. On the frontend, you will follow a signed operation from the client's RPC call through the bundler to finality, and prove it landed, failed or reverted the way it should. You will fork the chain to test against real state, deploy and call contracts from the command line, and turn what you learn into automated suites. You will work in a small, senior engineering team alongside an external wallet-infrastructure partner. You can tell a defect in our code from one in a partner SDK or in the chain itself — and you bring the evidence to show which. AI coding tools are part of how you work every day, and you set them up so the rest of the team gets the same leverage. ABOUT US Xsolla is a global commerce company with robust tools and services designed to help developers solve the inherent challenges of the video game industry. From indie to AAA studios, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in a strong belief in the future of video games, Xsolla is resolute in its mission to bring opportunities together and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as a merchant of record and has helped more than 1,500 game developers reach more players and grow their businesses worldwide. With more paths to profit and ways to win, developers have everything they need to enjoy the game. For more information, visit xsolla.com . WHAT YOU WILL WORK ON A consumer smart wallet built on account abstraction, so players can own and use digital items without managing keys or gas themselves. Integrations with an external wallet-infrastructure partner and with Xsolla's existing player products. Taking the wallet from testnet to a production launch on an Ethereum-compatible Layer 2. RESPONSIBILITIES Own the end-to-end test strategy for the wallet: sign-in, wallet creation, asset display, send and receive, and transaction confirmation on Xsolla ZK . Test account-abstraction flows: UserOperation construction and validation, bundler submission, EntryPoint execution, paymaster-sponsored gas, and session-key and signer behaviour. Test signing end to end: personal_sign and EIP-712 typed-data requests through the EIP-1193 provider, and signature validation by the wallet contract (ERC-1271), including before the wallet is deployed. Verify counterfactual deployment: that the address derived with CREATE2 from the factory, salt and init code matches the deployed wallet contract, on a forked or local chain, before it reaches mainnet. Deploy, call and inspect smart contracts from the command line to set up test state and reproduce defects. Use chain-forking and simulation tools to test against real network state without real funds, and trace failed transactions to their root cause. Validate the full transaction lifecycle — broadcast, inclusion, reorgs and finality — and its failure paths: reverts, failed UserOperations, insufficient balance, expired session keys, ownership changing mid-flight, and bundler errors. Reconcile what players see with on-chain state: indexer balances and NFT ownership against contract state, including when the indexer lags or diverges, and the account-to-wallet records behind Xsolla ID. Test transfers and approvals across ERC-20, ERC-721 and ERC-1155, including partial ERC-1155 quantities and safe transfers into contract wallets. Write acceptance tests for a partner's wallet SDK and contracts, and report integration defects with the evidence needed to route them to the right owner. Build and maintain automation: Playwright for wallet UI flows, and scripted on-chain checks in TypeScript that run in CI. Set up and maintain AI tooling in the test repositories (Claude Code, Codex, Cursor: rules, context, harness) so QA and engineers use it effectively. Plan and run testnet-to-mainnet release validation, including contract deployment verification and post-deploy smoke checks. Work with security on signing, key handling and key-export flows, and test for signature replay, typed-data phishing and token approval abuse. Mentor QA engineers who are new to Web3, and raise on-chain testing practice across teams. QUALIFICATIONS Required experience Bachelor's degree in Computer Science, Software Engineering, Information Systems or a related field (or international equivalent). 6+ years in software testing or quality engineering, including 2+ years of hands-on testing on EVM -based products. Web3 libraries and tooling Hands-on work with viem and wagmi (ethers.js also counts): reading contract state, sending transactions, and decoding events and revert errors from test code. Deploying and interacting with smart contracts from the command line with Foundry (forge, cast, anvil) or Hardhat; able to read Solidity well enough to know what a contract is meant to do. Chain forking and simulation with Anvil, Tenderly or similar tools, and tracing a failed transaction from a block explorer or transaction trace down to its revert reason. On-chain fundamentals A working model of Ethereum transactions: nonces, gas, receipts, events and logs, reverts, reorgs and finality — including the gap between a sequencer confirmation and L1 finality on a rollup — and how indexers can lag or diverge from chain state. Token standards: ERC-20, ERC-721 and ERC-1155 mechanics, including approvals and the safe-transfer callbacks a contract wallet must implement to receive NFTs. How wallet signers work: EOAs, embedded wallets and smart accounts; personal_sign (EIP-191) and typed data (EIP-712); the EIP-1193 provider; signature validation for contract accounts (ERC-1271). Practical understanding of account abstraction (ERC-4337): UserOperations, bundlers, the EntryPoint, paymasters, counterfactual deployment and CREATE2 address derivation, and session keys. Wallet security basics: signature replay and cross-chain replay, phishing via typed-data signing, and token approval abuse — and how to design test cases that catch them. Testing and automation Test automation in TypeScript or JavaScript, and UI automation with Playwright or a similar framework. API testing over REST and JSON- RPC , including bundler methods (eth_sendUserOperation, eth_estimateUserOperationGas, eth_getUserOperationReceipt), and basic SQL. Daily hands-on use of AI coding tools (Claude Code, Codex, Cursor) for test design, automation and review — generating test cases from specs, analysing logs and transaction traces — including configuring them for a repository. Ways of working Able to run complex, high-impact testing with minimal supervision and wide latitude for independent judgment. Excellent written and spoken English, and proven collaboration in cross-functional teams across time zones. Preferred Experience on a wallet, decentralized exchange or NFT marketplace. ZK Stack and zk -rollups: native account abstraction and paymaster flows on zkSync-family chains, and how finality, gas and EVM compatibility differ from Ethereum mainnet. Embedded, MPC or white-label wallet SDK integrations. EIP-7702 delegation, and ERC-6492 signature validation for accounts that are not yet deployed. Writing on-chain tests in Foundry, including fuzz and invariant tests; familiarity with OpenZeppelin contracts and the ERC-4337 reference implementation. Consumer-scale or gaming products. Reading Go. Load and performance testing of high-volume transaction flows, for example with k6. BENEFITS We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO , and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we're not just building a business; we're cultivating a community that values creativity, collaboration, and the transformative power of play. EQUAL EMPLOYMENT OPPORTUNITY STATEMENT Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act. CRIMINAL HISTORY CONSIDERATION For the Senior QA Engineer, Web3 (Smart Wallets), we will conduct a background check that may include the following: Criminal history check Employment verification Education verification Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com. By submitting the following job application form, you consent to Xsolla processing your data for career-related inquiries and potential employment opportunities. We process your data in accordance with the Xsolla Privacy Notice for Job Applicants. Please direct any inquiries regarding your data privacy to careers@xsolla.com.

Location: New York Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across liquid asset classes worldwide. We are a technology- and data-driven group that applies a scientific approach to investing. Our collaborative culture brings together research, technology, and trading expertise to solve complex challenges and deliver high-quality returns. We are looking for a Senior Technical Incident Manager to lead business-critical technology incidents for QRT’s US broker-dealer operations. You will coordinate recovery across systems supporting trading, research, execution, and risk while strengthening operational resilience. Your Future Role within QRT · Lead major incidents from triage and escalation through service restoration and recovery validation. · Coordinate technical teams, third-party providers, and regional Incident Managers throughout the incident lifecycle. · Assess business impact, prioritise recovery, and communicate clearly with stakeholders and senior leadership. · Maintain accurate incident records, timelines, and decision logs in designated ITSM tools. · Lead post-incident reviews, root-cause analysis, and remediation of recurring issues. · Improve incident processes, controls, metrics, tooling, workflows, and automation. · Partner with Technology, Operations, Risk, and Compliance on regulatory requirements, audit readiness, business continuity, and operational resilience. Your Present Skillset · 10+ years of experience in technology operations or service management within financial services or trading. · Hands-on experience in production engineering, SRE, application support, or infrastructure operations. · Proven ability to lead major incidents and drive timely, controlled recovery. · Strong knowledge of trading systems, service dependencies, failure scenarios, and change management. · Experience leading root-cause reviews and improving incident processes and controls. · Experience supporting engagement with US regulators, including the SEC and FINRA. · Clear communication with technical teams, trading stakeholders, and senior leadership under pressure. Nice to Have · Python or shell scripting, observability platforms, or incident workflow automation. · Familiarity with ServiceNow or Jira Service Management. · ITIL 4 Foundation certification or equivalent. Base salary range for this position is $180,000 to $250,000 per year. QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE The Robotics Applied Research Lead establishes and leads Humanoid’s AI research and engineering function. You decide which Physical AI data problems we work on, define how we test them, and stay directly involved in the most important technical work. You connect four areas that often sit apart: 1. Multimodal and embodied data 2. Transformer-based models and how data impacts robot policies 3. Rigorous offline and real-world evaluation of policies 4. Deployment of models in the data ecosystem This is a player-coach role. In the first year, at least half of your time is direct technical work: designing models and experiments, reviewing or writing code, inspecting data, debugging training, examining failures, and reviewing robot rollouts. You will also build a small research and engineering team. Add people only when the work requires them. MANDATE Turn Humanoid data and technical access into measurable advances in Physical AI systems. You own the answers, and the evidence, to questions such as: - Which model families should we train, adapt, or evaluate? - Which data produces meaningful gains in robot performance? - What coverage, sensors, annotations, and quality controls do the models require? - Which offline measurements predict real-world robot performance? - Where should we adapt existing open models rather than train from scratch? - What should Humanoid build itself, and what should it reuse or obtain through partners?   WHAT YOU'LL DO - Set the technical direction: Define a focused research and engineering roadmap. Select a small number of high-value bets with clear hypotheses, baselines, milestones, and stop criteria. Decide what we build, adapt, license, or access through partners. Drop work that no longer has a strong case. Likely scope includes vision-language-action models, multimodal Transformers, robot foundation models, action representation, imitation and reinforcement learning, world models, cross-embodiment transfer, data-efficient adaptation, and robot-policy evaluation. - Own Transformer research and engineering: Design, adapt, train, and evaluate Transformer-based systems for embodied tasks. Make the architecture and training decisions yourself. Start from strong existing models and baselines. Train from scratch only when evidence supports the cost. Build or review the critical code. - Connect models to data strategy: Define the data needed to train and evaluate the selected models. Specify sensors, modalities, annotations, mixtures, and quality controls. Measure the effect of data quality, diversity, and composition on model behavior. Distinguish data volume from data value. You set technical data requirements; you do not run annotation workforces or field collection. - Own evaluation: Establish offline and real-world evaluation systems, baselines, held-out conditions, and release gates. Guard against leakage, overfitting, and weak success definitions. Compare offline metrics with real-robot outcomes. A benchmark score alone is not a successful result. The evaluation must support a decision. - Move work onto physical systems: Take projects from problem definition through training, hardware integration, and real-world testing. Design safe test plans and staged deployment. Analyse failures across data, perception, model, control, hardware, and environment. Validate material claims on physical systems. - Build a small technical team: Recruit a few complementary researchers and engineers. Lead architecture, experiment, code, and failure reviews. Keep the team focused on validated results, not paper count, benchmark theatre, or headcount. - Represent the function and own responsible development: Explain the strategy to customers, partners, and investors. Convert customer needs into testable technical requirements. State uncertainty and limits clearly. Define safety constraints, supervision, and rollback paths for physical trials. Require reproducible evidence before making capability or safety claims.   WHAT WE'RE LOOKING FOR - Deep, direct Transformer expertise: This is a hard requirement. You must have personally made material architecture or training decisions in one or more substantial Transformer-based systems, such as vision Transformers, VLMs, VLAs, multimodal foundation models, Decision Transformers, diffusion Transformers, video Transformers, world models, or Transformer-based perception, planning, or control. You should be able to explain, in detail, how you represented inputs and outputs, tokenized data, fused modalities, structured attention and temporal context, chose losses, built the data mixture, distributed and monitored training, diagnosed failures, and what you personally changed and why it affected task performance. Using hosted model APIs, prompting language models, or running an unchanged public training recipe does not meet this requirement. - Physical AI or embodied-system experience: You have worked on machine learning for a system that perceives or acts in the physical world: robotics, autonomous vehicles, drones, industrial automation, manipulation, mobile robots, humanoids, wearable or egocentric systems, or similar. At least one substantial project progressed beyond an offline dataset into a real or operational physical system. Simulation-only experience is not sufficient unless you also owned credible sim-to-real transfer and physical validation. - Hands-on technical ability: You write and review high-quality Python. You work directly with PyTorch or an equivalent framework. You can read unfamiliar model and training code, design and debug experiments, inspect failures and rollout traces, work with large multimodal datasets, and make informed decisions about compute, memory, latency, and cost. - Technical leadership: You have set direction for important technical work: a research or engineering group, a major model or robotics programme, or a cross-functional project you owned. You have hired or mentored researchers or engineers, made architecture and resource decisions, stopped weak work, and taken a result into deployment. A management title is not required. Direct ownership is. - Evaluation, communication, and judgment: You design held-out tests, run controlled comparisons, find leakage and confounds, and report results with appropriate uncertainty. You separate evidence from belief, state what remains unknown, and reduce broad research questions to testable work. - Strong preference - Computer Vision: We are particularly interested in candidates who combine deep expertise in Transformer architectures with a strong background in computer vision. Relevant experience may include visual representation learning, vision-language models (VLMs), video and temporal modelling, object detection, segmentation, tracking, multi-view and egocentric vision, 3D and spatial reasoning, pose estimation, calibration, localisation, sensor fusion, or real-time vision systems. - Education: A PhD in machine learning, computer vision, robotics, computer science or a related field is valuable but not required. An equivalent record of original model work, technical leadership, and real-system delivery is sufficient. We care more about what you personally designed, trained, tested, and deployed than about a specific degree or number of years. NICE-TO-HAVE: - Technical expertise: Experience with VLA or robotic foundation models, action generation, diffusion or flow-matching policies, imitation learning, reinforcement learning, world models, robotic manipulation, cross-embodiment training, sim-to-real transfer, distributed training, ROS 2, or safety-critical systems. - Additional experience: Research publications, open-source contributions, early-stage company experience, or direct collaboration with technical customers and research partners.   WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Международный банк приглашает Директора направления DevOps для построения и масштабирования Внутренней Платформы Разработчика (Internal Developer Platform) как полноценного продукта.

Location: Prague, Czech Republic; Group career pages; Jobs.cz Workplace: Hybrid Forecasting at Rohlik currently drives operations across 12 fulfilment centres and 25,000 SKUs in five countries. Up until now, it has operated across local spreadsheets, individual judgement calls, and manual edits. It works, but it relies heavily on personal memory, lacks formal governance, and relies on manual routines. As we continue to scale Europe’s leading online grocery delivery service, we are establishing Integrated Business Planning (IBP)/Sales and Operations Planning (S&OP) as a brand-new Group department. The mission is to transform our current forecasting into an automated, governed, and scalable planning capability. As Head of Demand Planning & S&OP, you will build this function from the ground up. You will own the Group demand forecast, establish the global S&OP cadence, build and lead the team, and work hand-in-hand with BI, Product, and Engineering to replace manual routines with modern, automated tooling. Why this role is exciting - Build from the ground up: This is a build role, not a position where you inherit an established setup. You will define the operating model, set governance across five markets, and recruit your own team. - Direct C-level impact: You will stay close to the numbers daily, owning the daily forecast update delivered directly to the CEO, while framing strategic scenarios and trade-offs for executive decision-making. - Automation & product ownership: Rohlik is an AI-first company. You will partner directly with BI and Engineering to automate planning inputs, create override logs, and launch automated plan-change notifications. - Cross-functional authority: You won't just compile numbers. You will work at Director level to challenge Marketing uplifts, Commercial pricing, and Ops capacity, ensuring alignment across Commercial, Ops, and Finance. - Multi-country scale: You will shape planning standards across all our active markets: the Czech Republic, Germany, Austria, Hungary, and Romania. What you will own and deliver - Build the department: Hire and develop the IBP/S&OP team, transition from single-person routines to a documented, resilient team structure with no single point of failure. - Demand forecast & executive briefing: Own the Group demand forecast end-to-end and personally deliver the daily operational forecast brief to the CEO. - S&OP cadence & operating plan: Establish the Group S&OP cycle, consolidating commercial, operational, and financial commitments into a single constrained operating plan. - Governance & standards: Define planning responsibilities, KPI definitions, approval thresholds for manual adjustments, and escalation rules across CZ, HU, RO, DE, and AT. - Automation roadmap: Act as the business owner for custom planning products, driving the rollout of mass uploads, automated locks, override logging, and instant plan-change alerts to Ops and Supply. - Cross-functional alignment: Partner at Director level with Marketing, Commercial, Supply, Fulfilment, Last Mile, Finance, and BI, reconciling operational plans with financial outlooks. - Forecast accuracy & stability: Drive plan attainment and forecast value added over statistical baselines, maintaining high forecast accuracy (targeting ≥ 98% on orders and orderlines). What we are looking for - Proven leadership in planning: 5+ years of progressive experience in Demand Planning, S&OP, Integrated Business Planning, or Supply Chain operational planning. - Build track record: Demonstrated experience building or re-platforming a planning function from scratch — including team, processes, and tools. - Automation mindset: Direct experience driving the automation of manual planning routines alongside BI, Data, or Engineering teams. - Executive presence: Ability to distil complex, multi-market data into clear, concise updates for the CEO under tight deadlines. - Multi-market oversight: Proven track record running S&OP or demand reviews across multiple countries, sites, or business units. - Financial & commercial acumen: Strong understanding of service, cost, and cash trade-offs to reconcile operational plans with budget requirements. - Hands-on approach: Willingness to balance strategic function-building with daily operational detail and direct ownership of key briefings. - Languages: Fluent English is required. Knowledge of Czech, Slovak, German, or Hungarian is an advantage. Preferred qualifications - Background in online grocery, perishables, or fast-moving, high-SKU retail environments. - Experience acting as a product owner for internal or custom-built planning tools working alongside ML and Product teams. What’s in it for you - Fair reward - You’ll get a strong fixed salary — no bonus games, no politics. Great work is rewarded clearly and fairly. - Good food every day - You’ll enjoy a free lunch every day and fresh fruit & veggies in the office. Because good food fuels great work. - Life, not just work - You’ll have real flexibility – three days in the office, 2 days Home Office where it suits you. And unlimited paid vacation based on trust. - Personal growth - You’ll grow as fast as Rohlik does. Every challenge is a chance to learn and make an impact. - Real impact - What you do here matters. You’ll see your work changing how people eat and live — from day one. - Recognition among colleagues - Your effort won’t go unnoticed. You can recognise others (and be recognised) through peer credits to use in our internal cafeteria. - Xtra membership - You’ll get free Xtra membership and 10% cashback on everything you buy on Rohlik.cz http://Rohlik.cz. - Sport & wellbeing - You’ll stay active with company sports challenges or a subsidised Multisport card. - A team that sticks together - You’ll work with people who move fast, support each other and celebrate wins together. - If this sounds like you…You’re someone who takes ownership, acts fast and gets things done. Ready to bake something great with us? #LI-FK1

Location: United States ABOUT THE TEAM The EEE Parts Engineer works cross-functionally in support of hardware programs across the company. You will partner closely with Electrical Engineers, Quality Engineers, Supply Chain, and Program Management to ensure that every electrical, electronic, and electromechanical (EEE) component used in flight and mission-critical hardware meets the reliability, screening, and quality requirements demanded by high-reliability aerospace and defense programs. ABOUT THE JOB We are looking for an experienced EEE Parts Engineer to join us on a contract basis, owning parts engineering across one or more hardware programs for the duration of the engagement. In this role, you will work with Electrical Engineers to select and qualify parts for new designs, with Quality Engineers to define screening, inspection, and test requirements, and with Supply Chain to select and monitor part suppliers. You will build and maintain parts lists and screening plans, review contractual and customer requirements for parts impacts, shepherd nonstandard parts through internal and customer approval processes, and support root-cause investigations when parts fail during test. This role requires both deep technical knowledge of EEE parts and the collaboration skills to work effectively across engineering, quality, and program disciplines. This is a contract position with a defined period of performance. Contract duration and any extension options will be discussed during the hiring process. WHAT YOU'LL DO Parts Selection & Screening Plans: Develop and maintain the program's parts selection and screening plan, defining acceptable part classes, screening levels, and qualification requirements for EEE parts used in the design. Parts List & Baseline Management: Build and maintain a master parts list (preferred/approved parts list) tracking manufacturer, part number, screening level, qualification status, and approved alternates for every part used, including obsolescence and lifecycle tracking. Requirements Flow-down: Review statements of work, specifications, and contractual documents to identify EEE parts requirements, and flow those requirements down to design teams and suppliers alongside viable alternative part solutions. Supply Source Selection: Support evaluation of component manufacturers and distributors for quality, reliability, and supply-chain integrity, including authorized distribution and anti-counterfeiting controls. Nonstandard Part Approval: Prepare and submit nonstandard part approval data packages (qualification data, manufacturer reliability data, process-change evaluations), and present/defend them to an internal or customer parts control board. Part Qualification & Test Data Review: Review incoming part test data and qualification reports against program requirements, including oversight of Destructive Physical Analysis (DPA) lot-sample teardowns and Prohibited/Restricted Materials Analysis (PMA) dispositions. Failure Analysis & Corrective Action: Support investigation of EEE parts that fail incoming screening, board-level test, or system-level test; interface with failure analysis labs to determine root cause and drive corrective action. Obsolescence & Advisory Monitoring: Monitor industry alert/advisory systems (e.g., GIDEP) for notices affecting parts used on the program, and assess and disposition the impact on existing designs, inventory, and in-process procurements. Cost & Schedule Support: Estimate and track the cost and schedule impact of parts screening, qualification, and procurement activities, and support proposal efforts with EEE parts cost, risk, and schedule inputs. REQUIRED QUALIFICATIONS Education: Bachelor's degree in Electrical Engineering or a related technical field, with approximately 5 years of applicable industry experience (or a Master's degree with approximately 3 years). EEE Parts Knowledge: Strong working knowledge of EEE parts, including hermetic devices and plastic encapsulated devices, and the industry standards and military specifications that govern them. Screening & Qualification Standards: Familiarity with MIL-STD-883 and MIL-STD-750 (test methods) and MIL-PRF-38534/-38535/-19500 (hybrid, integrated circuit, and semiconductor device specifications). DPA & Failure Analysis: Experience with or working knowledge of Destructive Physical Analysis (MIL-STD-1580) and interfacing with part failure analysis labs to support root-cause investigations. Communication: Ability to produce clear, concise written and verbal technical reports for engineering teams, management, and customers. Cross-Functional Collaboration: Demonstrated ability to work effectively across Electrical Engineering, Quality Engineering, Supply Chain, and Program Management. Availability: Ability to begin the contract engagement promptly and commit to the expected period of performance. Export Control: U.S. Person status is typically required for roles accessing export-controlled data; eligibility to obtain and maintain a security clearance may also be required depending on program. PREFERRED QUALIFICATIONS Familiarity with MIL-PRF-55681, MIL-PRF-55342, and MIL-PRF-55310 (chip capacitor and resistor specifications). Experience monitoring and dispositioning GIDEP (Government-Industry Data Exchange Program) alerts and advisories. Experience performing or reviewing Prohibited/Restricted Materials Analysis (PMA), including tin-whisker and wire-bond material risk assessment. Experience supporting part qualification for space, launch vehicle, or other harsh-environment defense programs. Experience preparing data packages for, or presenting to, an internal or customer parts control board. Experience supporting Material Review Board (MRB) disposition of nonconforming parts and materials. Prior experience working in a contract or consulting capacity within aerospace and defense environments.