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Location: New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We are looking for an IT Support / Operations Engineer to join Baseten as we continue to scale our IT team. In this role, you will play a critical part in bringing our technical support entirely in-house to provide a seamless, high-touch experience for all Baseten employees. As we continue to scale, you will be the primary point of contact for day-to-day technical issues, allowing you to have a direct impact on our team's productivity and overall office environment. This position is ideal for a hands-on problem solver who enjoys a mix of hardware and software troubleshooting, user lifecycle management, and maintaining the physical IT infrastructure of a modern office. While you will focus heavily on elevating our internal support standards, you will also assist with systems administration and workflow automation as our company evolves. This is a hybrid role based out of our San Francisco or New York office, following our standard policy of three days per week in-person to ensure our physical office and AV systems remain high-performing and reliable.   RESPONSIBILITIES - Serve as the escalation point for day-to-day technical support, diagnosing and resolving hardware and software issues across our Mac and Windows fleet - Manage user lifecycle administration including provisioning, deprovisioning, and access management across all systems and services - Own the IT onboarding experience for new employees — from laptop setup and account configuration to a smooth first-day experience - Maintain and continuously improve office IT infrastructure to ensure a reliable, high-performing environment for all employees - Build and maintain a knowledge base of self-serve resources to reduce ticket volume and empower users - Manage IT asset procurement, inventory tracking, and vendor relationships - Support new office buildouts and contribute to broader workplace IT planning as we scale - Identify opportunities to automate workflows and eliminate inefficiencies across IT operations - Adapt to the evolving needs of a fast-growing company, taking on new challenges as they arise - Systems administration, including managing admin-level access, configuring user permissions, and performing routine maintenance across cloud-based services.   REQUIREMENTS - Strong working knowledge of Google Workspace, MDM platforms (e.g. Kandji), IdM/SSO solutions (e.g. Okta), and video conferencing tools - Proven experience administering macOS at scale, with solid working knowledge of Windows environments - Hands-on experience with automation tools and a track record of streamlining IT processes and workflows - Excellent communication skills with a genuine passion for delivering great support experiences - Strong organizational skills with the ability to manage multiple priorities in a fast-paced, ambiguous environment BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Toronto, Canada We’re partnering with a growing technology company focused on making roads safer through AI-powered video telematics. Its platform combines edge AI, dash cameras, real-time alerts, video analytics, and driver coaching to help commercial fleets improve safety, reduce risk, and operate more efficiently. The company partners with telematics service providers, OEMs, and other mobility businesses across global markets, providing flexible, hardware-agnostic technology that can be integrated into existing fleet solutions. As the business continues to expand, they’re looking for a Partner Success & Sales Enablement Specialist to strengthen partner relationships, support commercial initiatives, and help partners successfully bring the technology to market. Requirements Job Description The Partner Success and Sales Enablement Specialist plays a key role in ensuring our partners are equipped with the knowledge, resources, and support they need to successfully sell, deploy, and support our solutions. This role combines partner onboarding, sales enablement, training, content creation, and cross-functional project coordination. The ideal candidate is an excellent communicator who enjoys learning new technologies, simplifying complex concepts, and creating engaging content that enables partner success. Requirements ‍ Desired Skills: Experience: 1-3 years in video telematics/telematics industry. Previous experience in telematics, video telematics, fleet technology, or a related industry is preferred Excellent verbal and written communication skills. Strong presentation and facilitation skills. Highly organized with strong attention to detail. Ability to quickly learn and explain technical concepts. Experience creating presentations and customer-facing content. Comfortable managing multiple priorities in a fast-paced environment. Experience in customer success, sales enablement, training, or partner management is preferred. ‍ Responsibilities: 1. Partner Enablement Deliver onboarding and training sessions for new and existing partners. Develop and maintain onboarding guides, training materials, and partner documentation. Support partners throughout their onboarding and enablement journey. Act as a trusted resource for partner questions and product guidance. ‍ 2. Sales Enablement Create and maintain sales presentations, battlecards, product guides, and demo materials. Develop training content for internal teams and partners. Collaborate with Product and Marketing to ensure enablement materials remain current. Assist in communicating new product features and updates. 3. Cross-Functional Collaboration Work closely with Sales, Product, Marketing, Support, and Engineering teams. Coordinate partner enablement activities and product launches. Gather partner feedback and communicate insights internally. Track enablement initiatives and follow up on action items. 4. Product Knowledge Develop a strong understanding of our platform and solutions. Translate technical capabilities into clear customer value and business outcomes. Stay informed on new product releases and competitive offerings. Benefits Benefits We are growing fast, which means you will have a key role in shaping our future. We are profitable – which is a really big deal in these times! Energetic and positive atmosphere where talented people are working together with a single-minded focus on solving customer problems. Opportunity to work on cutting-edge solutions that incorporate the latest innovations in computer vision, AI, Android, iOS and full stack web development. A company where employees come before customers – we are growing fast having grown headcount by 50% in the last one year Stock options and great benefits (including health insurance for you and your dependents).

Location: Kazakhstan; Georgia; Poland; Serbia; Spain Crystalia Glass LLC is a leading provider of premium glass products, trusted by renowned clients such as SpaceX, Nike, Starbucks, Bank of America, Yves Saint Laurent, and many others. Founded in 2017 in New York, the company now operates across the United States, delivering high-quality glass solutions for both residential and commercial projects. We are looking for Business assistant to CEO with Russian (C1+) and English (C1+) Employment Type: - Full-time 8.30 am - 5 pm, NY (ET zone) . - Remote work. - B2B contract (sole proprietorship status or corporate entity) . Executive Support & Coordination Manage the CEO’s daily, weekly, and monthly schedules; organize meetings, calls, and business trips. Prioritize tasks, manage deadlines, and ensure the CEO’s time is used efficiently. Anticipate the CEO’s needs and prepare relevant information, materials, or reports in advance. Filter and organize incoming communication; draft correspondence and reports in English and Russian. Maintain confidentiality and professionalism in all aspects of the role. Business & Administrative Support Prepare presentations, summaries, and analytical reports for decision-making. Coordinate internal and external communications on behalf of the CEO. Support ongoing company projects: monitor progress, collect data, prepare updates. Manage interactions with suppliers, contractors, and partners. Keep records, documentation, and administrative files in order. Open and renew business licenses as required. Coordinate with insurance brokers to ensure proper endorsements, riders, and coverage extensions. Issue and track Certificates of Insurance (COIs) per contract and insurance requirements. Prepare and submit applications for Contractor’s Licenses in states where the company plans to operate. Monitor and coordinate vehicle registrations, renewals, and insurance coverage for the company fleet. Travel & Event Management Plan and organize business trips, including flights, accommodation, logistics, and itineraries. Coordinate participation in business meetings, exhibitions, and conferences. Handle visa processes and other documentation related to international travel. Internal Communication & Company Coordination Communicate with the CEO’s direct reports and partners on his behalf. Follow up on meeting outcomes and ensure tasks are completed on time. Support the CEO in maintaining clear and positive communication across departments. Strategic & Advisory Support Conduct market, business, and competitor research when required. Track and summarize company performance data and KPIs for the CEO. Act as an advisor and communication bridge between the CEO and key stakeholders. Help identify process improvements and opportunities for efficiency. Personal & Lifestyle Support (limited scope) Support personal planning and balance between work and private matters when necessary. Handle selected personal arrangements or errands on behalf of the CEO in a professional manner. Requirements Higher education in Law/International business/International relations or similar Minimum 3 years of experience as a Business Assistant, Executive Assistant, or similar role in a dynamic business environment. Strong understanding of business operations, corporate communication, and project coordination. Fluent English (C1 level +) and Russian (written and spoken). Experience working for a US company with operations in the USA (will be a big plus) Excellent time management, prioritization, and organizational skills. Ability to make decisions independently and maintain confidentiality. Professional demeanor and strong interpersonal communication skills. Proficient with office software and digital tools (Google Workspace, MS Office, Zoom, AI assistants and others). Basic understanding of finance, budgeting, and reporting is a plus. Personal Qualities High energy, strong motivation, and proactive attitude. Attention to detail and ability to anticipate needs before they arise. Strategic and analytical mindset with a focus on solutions. Flexibility, adaptability, and a calm approach under pressure. Ethical, loyal, and committed to maintaining confidentiality and professionalism. Benefits Fully remote work (you can be located anywhere in the world) 8:30 AM - 5 PM (ET) NY Competitive compensation package (will be discussed with successful candidates). Benefits: paid vacation days + sick leave. Opportunity to work directly with the CEO and top management. Exposure to US market business operations and strategic projects. Dynamic environment with opportunities for professional growth.

Location: San Francisco, CA | New York City, NY | Seattle, WA 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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. The RL Scaling team works on how RL scales: what happens to throughput, stability, and learning efficiency as models get larger, episodes get longer, and compute grows by orders of magnitude, and what has to change in our algorithms and systems to keep getting returns from that scale. This role sits squarely across research and engineering. You'll develop next-generation architectures and RL algorithms, take them from a small-scale result to a frontier-scale run, and understand every place they behave differently along the way. You'll build the systems that set how fast the team can iterate: how many experiments, at what scale, and how quickly we can trust the results. And you'll work on Anthropic's largest and fastest RL runs, where the gap between a good idea and a working one is often a problem no one has solved yet. Key responsibilities Study how RL training and sampling scale with model size, context length, and compute, and find the algorithmic and systems changes that keep scaling efficient Develop next-generation model architectures and RL algorithms, and make them run efficiently at frontier scale Take promising small-scale results to frontier-scale runs, and diagnose why they behave differently when they get there, whether the cause is numerical, algorithmic, or systemic Build the experimental infrastructure that sets research velocity: fast, reproducible comparisons of architecture and algorithm variants at meaningful scale Own end-to-end performance of our largest RL runs, from research code down to the hardware Build performance and cost models for proposed architecture and algorithm changes, and use them to decide which ideas get scaled Investigate training dynamics at scale, including instabilities, divergence, and throughput regressions, and trace them to root cause Minimum qualifications Deep familiarity with modern transformer language models, including their architecture, training dynamics, and the behavior of large-scale optimization Hands-on experience training large models in a distributed setting, including the tradeoffs between data, tensor, and pipeline parallelism A track record of original technical work in ML training or systems, such as new methods, architectures, or optimizations, demonstrated through research, open-source, or production impact Ability to design rigorous experiments at scale, including baselines, ablations, and enough statistical care to trust a result that costs real compute Ability to reason quantitatively about the compute, memory, and communication costs of a model or algorithm Strong programming skills in Python and JAX or PyTorch, and comfort reading and changing code at every layer of the stack Preferred qualifications Research experience in reinforcement learning, optimization, or large-scale training, published or otherwise Experience developing RL algorithms for language models Experience with scaling laws or other quantitative models of training efficiency Experience designing or modifying transformer architectures beyond standard configurations Experience scaling training to large fleets of accelerators and debugging the problems that only appear at scale Deep understanding of numerics in large-scale training, including low-precision formats and sources of instability Familiarity with how GPU or TPU performance characteristics shape architecture and algorithm choices Experience with C++ or Rust Representative projects Characterize how a new RL algorithm's throughput and learning efficiency change from small models to frontier scale, and fix what breaks Develop a new attention variant, get it working at full scale, and measure how its quality and throughput compare to the baseline Prepare our next largest-ever RL run: find what breaks when model size, context length, and compute all grow at once, and fix it before launch Trace a loss instability that only appears past a certain scale to its root cause, and work out whether the fix belongs in the algorithm, the numerics, or the system Build a model that predicts the throughput and cost of a proposed architecture change before anyone writes the kernel 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: $500,000 — $850,000 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. 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 | New York City, NY | Seattle, WA 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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. How well that system holds together determines how much of our compute turns into learning, and how quickly the team can try the next idea. As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit. That might be scheduling and placement, data movement between components, running large numbers of sandboxed environments, storage and checkpointing, networking, fault tolerance, autoscaling, or the observability that tells us what a run is actually doing. We're looking for generalists: engineers who can move between these layers, reason from first principles about a system they haven't seen before, and pick the problem that matters most rather than the one closest to their prior experience. Our system changes as fast as the research does, correctness under failure matters as much as throughput, and the best solutions often come from understanding the ML workload well enough to know which guarantees it actually needs. Strong candidates have built and run large distributed systems, care about getting the details right, and want to apply that experience to a workload that is very large, very heterogeneous, and changing quickly. Key responsibilities Design, build, and operate the distributed systems that run RL at scale, across training, sampling, and environment execution Find and remove whatever currently limits the system, whether it's scheduling, data movement, storage, networking, or coordination Build fault tolerance into every layer: failure detection, isolation, and recovery that keep long-running jobs making progress without human intervention Design resource management and autoscaling so that compute follows demand as a run's needs shift Build observability that makes it possible to understand what a run is doing and why it slowed down, stalled, or produced unexpected results Build automation that detects and remediates common problems, and design interfaces that let engineers and automated tools operate runs safely Work with researchers and performance engineers to make sure systems changes preserve training correctness and don't introduce subtle nondeterminism Remove classes of failure at their source through incident review, testing, and redesign, and write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems in production Deep understanding of distributed systems fundamentals, including consistency, coordination, consensus, failure modes, and recovery Ability to reason quantitatively about throughput, latency, and resource costs across compute, memory, storage, and network Experience debugging complex failures across many hosts and services, including failures you can't reproduce locally Strong written communication, including design documents and incident writeups Preferred qualifications Experience running ML training or inference infrastructure at scale Experience across several layers of the stack, such as scheduling, storage, networking, and orchestration Experience building schedulers, autoscalers, or resource management systems Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience with high-performance networking, RDMA, or collective communication libraries Experience building observability or automated remediation for large fleets Experience with async Python frameworks such as Trio or asyncio Familiarity with reinforcement learning or large language model training workloads Representative projects Design a scheduler that places training, sampling, and environment work across a heterogeneous cluster while respecting network topology and failure domains Build a failure detection and recovery system that lets a long-running job survive host and network failures with minimal lost work Scale environment execution substantially without increasing tail latency for the training step Design an autoscaling policy that rebalances compute across components as a run's bottleneck shifts Build a diagnostics system that explains why a run's throughput dropped and proposes a fix Trace a rare data corruption bug across many services to a race condition in a recovery path, and redesign the path so the class of bug can't recur Design the operational interface for a run so that automated tools can safely diagnose and adjust it under human oversight 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: $500,000 — $850,000 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. 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 Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Real-World Test Lab (RWTL) Physical AI doesn't get graded on a leaderboard. It gets graded on a factory floor at shift change, in a substation with no GPS, on a site where the lighting is wrong and the stakes are real. The Real-World Test Lab closes the gap between the benchmark and the field. We bring the customer's world inside our walls — their devices, their environments, their hardest conditions, and their definition of success — and make it the bar every release has to clear. As Niantic Spatial's first and most demanding customer, we push our reconstruction, localization, and spatial understanding to their limits, find where they shine and where they break, and turn that into evidence that shapes what we build next. It's a new team at the frontier of physical AI, and you'll help invent how the job is done. About the Role We're hiring a Hardware Operations Engineer with a robotics specialism, reporting to the Director of the Real-World Test Lab, to own the physical layer of our evidence. You'll manage our fleet of capture devices and robots, engineer the test environments and the instrumentation inside them, support the captures our data programs depend on, and run physical test sessions, including the real-robot side of our sim-to-real work. A physical run only counts as evidence if the hardware is characterized, the environment is controlled, the ground truth is trustworthy, and someone can reproduce the run months later. You'll build what makes that possible: fixtures, ground-truth references, calibration and data-offload tooling, and the integrations that feed physical runs into the same automated evaluation system as everything else. You engineer the conditions, not just the setup. When a physical result didn't match expectations, you've worked out whether the hardware, calibration, environment, or system under test was responsible. Then you built the rig, reference, or logging that kept the question from coming back. You know an uninstrumented physical test is an anecdote, and in the Lab you'll be the person who can say with authority whether a strange result is real. What Success Looks Like - 30 days: Fleet inventory and characterization baseline complete, safe operating procedures defined for current spaces, and first instrumentation gaps identified. - 60 days: First physical robot run executed with ground-truth instrumentation, documented well enough to repeat, with results in the Lab's evaluation system. - 90 days: Test environments in regular use with controlled, documented conditions; capture support running smoothly with our data acquisition team; and the physical side of sim-to-real running on a standing instrumented protocol. What You'll Do - Own and Characterize the Fleet - Manage our capture devices, sensors, and robots end to end: inventory, calibration, firmware, maintenance, logistics, and spares. Characterize what each platform can and cannot do, so a device's limits are a known quantity rather than a surprise inside a result. - Engineer the Physical Test Environments - Design, build, and operate the spaces we test in, covering layout, lighting control, markers, obstacle configurations, and survey-grade ground truth references, across our office, rented or workplace-services-supported space, and partner or customer sites. Make each environment a controlled variable rather than an improvisation. - Build the Instrumentation - Create the rigs, mounts, references, and measurement setups that turn a physical run into quantitative data: trajectory ground truth, positional accuracy references, timing and synchronization across sensors, and automated condition logging. - Integrate Physical Runs Into the Evaluation System - Work with the AI Automation Engineer so physical results flow into the same scorecards and comparisons as software-only evaluations, through automated data offload, run metadata, and structured condition capture rather than a spreadsheet and a folder of files. - Run the Physical Test Sessions - Execute robot runs and device-in-the-loop tests: robot bring-up, teleoperation, scripted trials, and the repetition that makes a result statistically meaningful rather than anecdotal. - Own the Physical Half of Sim-to-Real - When a scenario has been evaluated in simulation, engineer and execute its physical counterpart so the comparison is valid, matching environment, route, lighting, sensor configuration, and robot setup, and instrumenting the run so divergence is explainable rather than mysterious. - Own Safety - Define and maintain safe operating procedures for robots and powered equipment in our test spaces, and coordinate with workplace services, IT, Legal, and site owners on access and safety requirements. - Automate Your Own Work - Script the repetitive parts, including configuration, calibration checks, data offload, and condition logging, so setup time falls and a colleague can run a session without you. What You'll Bring - Hands-on engineering experience with robotic hardware, covering bring-up, integration, teleoperation, troubleshooting, and maintenance. Mobile or wheeled platforms preferred. - Built test rigs, fixtures, or instrumentation that produced quantitative measurements of a physical system's behavior. - Designed and run structured physical experiments, including ground truth methodology, and documented conditions rigorously enough for someone else to reproduce them. - Worked with sensor calibration, multi-sensor synchronization, and coordinate frame conventions, and understand how errors in each propagate into a result. - Strong Python and command-line proficiency, with a track record of automating hardware configuration, data offload, or test execution. - Managed hardware fleets operationally: inventory, firmware, calibration schedules, logistics, and repair coordination. - Practical safety experience operating powered equipment or robots around people. - A bachelor's degree in a relevant field, or equivalent experience. Nice to Have - Worked with ROS or ROS 2, including writing nodes or integrating sensor drivers. - Operated NVIDIA Isaac Sim or Isaac Lab as a user, running scenarios someone else authored. - Worked with professional capture hardware such as terrestrial laser scanners, NavVis or Leica systems, LiDAR, 360 cameras, or drones. - Established survey-grade or motion-capture ground truth for localization or navigation evaluation. - Supported photogrammetry, Gaussian splat, or 3D reconstruction capture workflows. - Run test operations at customer or partner sites, with the coordination and discretion that requires. Competencies - Engineering judgment about physical systems. You reason about error sources: calibration drift, timing offsets, mounting rigidity, lighting variation, floor surface. When results disagree, you form a hypothesis and design the measurement that settles it. - Hands-on and unfazed. You'd rather be in the space with the robot than reading about it. Cables, mounts, batteries, firmware, and a session that starts at 7am are all part of the job. - Meticulous about conditions. You instrument rather than remember. You know the value of a physical test lives in how precisely its conditions were captured. - Safety-minded without being slow. You take real responsibility for operating robots around people, and you build procedures where the safe path is also the fast path. - Builds for other people. Your fixtures, scripts, and procedures get used by colleagues without you in the room. - Comfortable in an unfinished environment. Much of this does not exist yet. You'll be selecting equipment, designing the first rigs, and defining how a space gets configured, with support but without a playbook. Compensation & Benefits Base salary range of $142,200 to $193,000. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: New York City, NY; San Francisco, CA; Seattle, WA 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 Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researchers to develop next-generation models Integrate new AI accelerator platforms and support inference for new model architectures Minimum qualifications Significant software engineering experience, particularly with distributed systems Results-oriented, with a bias towards flexibility and impact Willingness to pick up slack, even if it goes outside your job description Desire to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Preferred qualifications Experience with high-performance, large-scale distributed systems Experience implementing and deploying machine learning systems at scale Experience with load balancing, request routing, or traffic management systems Familiarity with LLM inference optimization, batching, and caching strategies Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure) Proficiency in Python or Rust Representative projects Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions of users reliably Contributing to new inference features Supporting inference for new model architectures Analyzing observability data to tune performance based on real-world production workloads Managing multi-region deployments and geographic routing for global customers 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: $320,000 — $485,000 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. 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: US, Boston, MA 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 We are seeking a Principal Product Cybersecurity Assurance Engineer with deep expertise in product security, threat modelling, and risk assurance for highly regulated electromechanical systems. In this role, you will lead the delivery of product cybersecurity across Humanoid's HMND 01 platform family — the Alpha Wheeled industrial robot and the Alpha Bipedal home robot — both powered by our KinetIQ VLM/VLA-based AI framework. Working alongside product, firmware, autonomy, and hardware teams as part of the Systems Engineering and Architecture Team, you will define and maintain the cybersecurity assurance strategy for all product security activities from first concept through post-market deployment. Security at Humanoid is an engineering discipline inseparable from functional safety and central to our mission of creating the world's most reliable, commercially scalable, and safe humanoid robots. To excel in this position, you must demonstrate the authority to influence security architecture decisions across complex, cross-functional programmes, the rigour to build defensible security cases for novel cyber-physical systems, and the leadership to grow and guide a cross team of security engineers operating at the frontier of robotics. WHAT YOU'LL DO - Team Leadership & Product Security Delivery - Lead and develop a cross-functional team of security engineers, maintaining accountability for the delivery of product security services within product teams throughout the HMND 01 development lifecycle. - Define product security requirements and advise development teams on suitable implementation standards, techniques, and toolchains for embedded and AI-enabled robotic systems. - Partner with cross-functional teams to develop security protocols, tools, and processes that keep HMND 01 technologies ahead of emerging threats — including attack surfaces specific to the KinetIQ AI inference pipeline and cloud-to-robot communication architecture. - Own and maintain key security artefacts for audit-ready cybersecurity documentation including Security Management Plans, Threat Analysis and Risk Assessment (TARA) reports, Risk Assessments, and Remediation Action Plans across both platforms. Security Assurance & Certification - Drive security assurance through the full product lifecycle, ensuring every HMND 01 design is robust, compliant, and resilient. Contribute to the continual improvement of security engineering capability across the organisation. - Ensure compliance with cybersecurity obligations under the EU Machinery Regulation 2023/1230 where cyber controls intersect with safety-critical functions and compliance to IEC 62443 (for industrial/OT product security), and the EU Cyber Resilience Act. - Provide independent Information Assurance (IA) reviews and risk assessments on complex, high-impact projects — with particular focus on cyber-physical systems where a digital compromise could result in physical harm to operators or end users. - Review and provide guidance on security risk assessments, risk mitigation plans, mitigation gap analysis, and security management documentation in support of system cybersecurity certification. Incident Response & Lifecycle Security - Establish and maintain a Product Security Incident Response (PSIR) process, encompassing coordinated vulnerability disclosure, patch deployment pipelines, and post-field incident analysis. - Define and oversee security monitoring requirements for deployed fleets, ensuring field data feeds back into risk files and security artefacts in line with post-market surveillance obligations. Commercial & Bid Support - Support the production of work package descriptions and cost estimates for product bids, services, and proposals that include product security scope. - Represent Humanoid's security posture in customer and partner engagements, including regulatory consultations and certification body interactions. WHAT WE'RE LOOKING FOR - Proven, hands-on experience with ISO 27001/27004/27005 and the NIST Risk Management Framework (RMF), applied to regulated hardware or embedded product programmes. - Experience owning a security risk management system for highly regulated, safety-critical products — with background drawn from automotive, commercial vehicle, or industrial automation environments. - Working knowledge of IEC 62443, with the ability to adapt ISO/SAE 21434 lifecycle methodologies to robotic or electromechanical product context. - Solid understanding of engineering development lifecycles and how the product cybersecurity specialism aligns with systems engineering, functional safety, and hardware/software co-development. - Ability to interpret Penetration Test reports and author Remediation Action Plans that address identified vulnerabilities in a structured, risk-prioritised manner. - Clear, structured communication skills — able to articulate complex security risk arguments to both technical engineers and executive stakeholders with equal confidence. Preferred: - Familiarity with Threat Analysis and Risk Assessment (TARA) or equivalent threat modelling methodologies (STRIDE, PASTA) applied to embedded or OT/IT convergent systems. - Understanding of secure-by-design principles for AI/ML-enabled systems, including securing inference pipelines, model integrity, and cloud-to-edge communication paths. - Exposure to CAN bus, Ethernet backbone, or wireless interface security in mobile, vehicular, or robotic systems. - Experience contributing to or establishing a Product Security Incident Response (PSIRT) process or coordinated vulnerability disclosure programme. - Knowledge of UL 4600, UL 3300, or ISO 13482 and an appreciation of how cybersecurity evidence integrates into safety case arguments. - Prior engagement with certification bodies (TUV, UL, BSI) or standards development organisations (ISO TC 184, IEC TC 65, SAE, IEEE RAS). WHAT WE OFFER - Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources. - Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays. - 401(k) retirement plan with 4% employer match. - Competitive equity: stock options with meaningful upside as we scale. - Free daily catered lunch, snacks, and drinks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives.

Location: Singapore ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB Mistral AI is seeking an Applied AI Engineer focused on robotics deployment. You will take state-of-the-art AI models and make them work on real robots, in real environments, for real customers. This is a hands-on role at the intersection of machine learning and physical systems: you will own the path from model to deployed autonomy, working alongside robotics engineers, ML researchers, and systems engineers to deliver end-to-end autonomous solutions across diverse use cases. WHAT YOU WILL DO - Integrate AI models with robotic hardware, sensors, and embedded systems, bringing modern perception and language-driven capabilities onto physical platforms. - Improve the robustness, reliability, and safety of robotic systems operating in real-world, unstructured environments. - Test and validate algorithms in simulation and in real-world deployments, moving fluidly between the two. - Analyze field data to improve model performance and system reliability, closing the loop between what happens on the robot and what happens in training. - Bring up, tune, and debug the autonomy stack — localization, mapping, navigation, and perception — on real hardware, from sensor calibration to real-time performance. - Develop and tune robot navigation behaviors — path planning, obstacle avoidance — so systems hold up in dynamic, cluttered, and partially observable environments. - Diagnose failures end-to-end: mapping drift, localization dropouts, perception edge cases, timing issues — and fix them. - Collaborate with robotics engineers, ML researchers, and systems engineers to deliver complete autonomous solutions for customer use cases, from prototype through production deployment. - Build and maintain the tooling needed for deployment, monitoring, and continuous improvement of deployed systems. ABOUT YOU - Bachelor's, Master's, or PhD in Mechatronics, Robotics, or a relevant discipline (e.g. Computer Science, Electrical or Mechanical Engineering). - Fluent in English with excellent communication skills. - Strong software engineering in Python and/or C++: clean, readable, high-performance code; comfortable working in and improving production codebases. - Knowledge of robotics frameworks such as ROS/ROS2. - Experience with robot perception and state estimation: SLAM, localization and mapping, path planning, sensor fusion, or computer vision. - Solid mathematical fundamentals — geometry, probability, and estimation — and the judgment to know when a hand-crafted algorithm beats a learned one. - Familiarity with simulation tools and robotics development environments (e.g. Isaac Sim, Gazebo, or similar). - Strong problem-solving skills and ability to work in interdisciplinary teams. - Comfortable with the messiness of the real world: hardware quirks, edge cases, and field surprises don't scare you. - Low-ego, collaborative, and eager to learn. - Doesn't need roadmaps. Ships. NICE TO HAVE - Experience deploying ML models on embedded or edge hardware (GPU/NPU inference, quantization, real-time constraints). - Hands-on experience with sensor modalities such as LiDAR, depth cameras, or IMUs, including calibration and time-synchronization. - Exposure to VLM/VLA models or other foundation-model approaches for robot perception and control. - Experience with navigation in GPS-denied or otherwise challenging environments, or with visual-inertial odometry. - Working knowledge of established autonomy tooling — e.g. Nav2, SLAM Toolbox, Cartographer, RTAB-Map, or AMCL — and knowing when to build versus reuse. - Experience with behavior trees, dynamic costmaps, or fleet-level navigation. - Contributions to open-source robotics or ML projects. - Experience with safety-critical or regulated deployment environments. - Track record of success through personal projects, professional projects, or academia. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: New York; San Francisco ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE ROLE Our Inference business works differently from a typical software business. What we can sell is capped by GPU fleet capacity, and what we earn depends on the blended cost of the GPUs serving each workload. Both can change week to week. This role sits between the people who run the fleet and the people who sell it. You will be the person who can answer, at any point in the quarter, three questions with real numbers behind them: 1. What do we have to sell? 2. What should we sell it for? 3. What do we make when we do? You will own the commercial data, models, processes, and operating cadence behind these decisions, partnering closely with the Head of Digital Native Sales and serving as the commercial operating lead across Sales, Data Science, Inference Infrastructure, Finance, and Product. This is a build role. Little of the commercial infrastructure you need exists today. WHAT YOU'LL DO Capacity and demand - Build and own an end-to-end inference demand forecast combining pipeline, contracted commitments, and consumption trends into a forward-looking view of expected demand. - Combine capacity signals with pipeline demand to show what is available to sell and surface shortages, unused capacity, and supply-demand mismatches. - Translate customer requirements into structured inputs that Data Science and Inference Infrastructure can use to assess workload impact and feasibility, and help prioritize opportunities by revenue, margin, fit, timing, and strategic value. Pricing and margin - Publish regular updates to GTM and Finance on available supply and recommended price, informed by market rates for provisioned throughput and per-token pricing. - Partner with Finance and Pricing to build rate cards, target prices, price floors, and discount guardrails GTM can act on. - Build and own margin sensitivity models showing how workload, utilization, contract structure, and discounting affect deal and portfolio economics. Data infrastructure and GTM telemetry - Build the commercial telemetry for Inference: usage, consumption patterns, expansion, churn signals, and other leading indicators of revenue. - Connect capacity and usage data with pipeline, contracts, pricing, and revenue, and build self-serve reporting that helps GTM, Finance, and leadership make capacity, pricing, and prioritization decisions. - Partner with Finance on long-range planning for Inference, connecting demand forecasts to capacity and capex planning. Core revenue operations - Own territory design, ICP definition, data-driven targeting, pipeline management, forecasting, and compensation plan design for the Inference and Digital Native segment. - Track competitive dynamics across inference providers and adjacent players, turning them into pricing and positioning input. Cross-functional leadership - Drive alignment across Sales, Data Science, Inference Infrastructure, Finance, and Product on demand, capacity, pricing, and economics. - Ensure customer demand reaches technical teams early enough to inform capacity decisions, and build a structured feedback loop from requests, adoption patterns, blocked deals, and losses into Product and Engineering. WHAT YOU'LL BRING Required skills and competencies - Experience in revenue operations, business operations, strategic finance, or investment banking in a business where cost of goods is real and variable — cloud infrastructure, compute, telco, logistics, or similar. Pure SaaS RevOps is not a fit on its own. - Strong SQL and comfort building your own data models: raw tables to dashboard, without waiting on a data team. - Demonstrated ability to build unit economics and margin models that other functions trust and use. - Enough technical fluency to hold a real conversation with infrastructure engineers about GPUs, utilization, serving efficiency, and capacity — or clear evidence you can get there fast. - Comfort operating with incomplete data, with a bias toward shipping a rough answer this week over a perfect one next quarter. - Strong cross-functional leadership and the ability to influence technical and commercial teams without direct authority. Ideal additional skills and competencies - Familiarity with the inference market: provisioned throughput, per-token pricing, batch vs. real-time serving, and how the major providers price. - Experience with consumption- or usage-based revenue models. - Salesforce, BigQuery, and BI tooling (we use Metabase). - Having sat between a technical team and a commercial team before, trusted by both sides. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Boston, MA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM The LangSmith team owns and builds LangChain's core platform for observability, evaluation, and production reliability of AI systems. From tracing and annotation to run rules, evaluations, and beyond, this team owns LangSmith end-to-end. If you want to define what great AI observability looks like at production scale, this is where that work gets done. ABOUT THE ROLE (Onsite in Boston) We’re looking to bring on an experienced frontend engineer to develop and enhance new features on LangSmith, our enterprise platform product for LLM application observability, testing, and debugging.   WHAT YOU WILL DO - Develop new user-facing features using React & Typescript - Build reusable components and front-end libraries for future use - Translate designs and wireframes into high-quality code - Optimize components for maximum performance across a vast array of web-capable devices and browsers - Collaborate with fullstack and backend developers and UX/UI designers, to enhance usability   WHAT YOU WILL BRING - Extensive front-end engineering experience with strong proficiency in React, JavaScript and TypeScript - Hands-on experience with front-end development tools like Babel, Vite, Webpack, NPM, and Yarn - Familiarity with REST APIs and experience working closely with fullstack and backend engineers - Knowledge of modern authorization mechanisms, such as JWTs - A passion for user experience, design and building clean, engaging, and intuitive interfaces - Strong written and oral communication skills, with the ability to explain technical concepts clearly and concisely to both technical and non-technical stakeholders - The DNA to thrive in a start-up, fast-paced environment. Views unstructured environments as an opportunity to figure out the most impactful work and help define the future success of the company - An ownership mind-set. You are self-driven and look for opportunities to make an impact. - Strong computer science fundamentals, ideally with a degree in computer science or related field   Annual salary range: $170,000-$235,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Foster City, CA Workplace: Hybrid Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. ABOUT THE ROLE Replit enables people to build software with AI. The infrastructure underneath that experience must make it straightforward to launch services, isolate workloads, and run reliable systems at scale. We're hiring a hands-on Engineering Manager to lead Cloud Infrastructure: the shared infrastructure as code (IaC), networking, storage, compute, and service mesh platforms that Replit's product and platform teams depend on. You'll lead and grow an existing engineering team building and operating these foundations, including Kubernetes, shared edge networking, service mesh and workload identity. This is a platform-building role with production accountability. You should be comfortable going deep on a design or incident while developing a team that does not depend on you for every decision. WHAT YOU'LL DO - Own the cloud-platform roadmap. Lead the team's IaC, networking, storage, compute, and service mesh platforms. Translate product, platform, reliability, and security needs into sequenced outcomes, balancing foundational investment, lifecycle work, and delivery commitments against the team's capacity. - Make infrastructure repeatable and self-service. Build maintained IaC interfaces for services, cells, connectivity, identities, and shared resources. Enable internal customer teams to provision infrastructure without bespoke coordination or dependence on individual experts. - Operate what the team builds. Own platform availability, upgrades, isolation, recovery, and incident remediation. Maintain clear SLOs, sustainable on-call coverage, and primary and backup owners for critical systems. - Stay technically engaged. Review designs and production changes, debug difficult failure modes, and use AI coding tools—including Replit—to prototype and automate. Apply rigorous review and verification to AI-generated infrastructure changes. - Build and grow a high-ownership engineering team. Coach engineers, develop technical leaders, set clear expectations, manage performance, and hire against agreed needs. Delegate meaningful ownership as the team grows. WHAT YOU'LL BRING - Demonstrated engineering management. You have led and developed engineers, made prioritization and performance decisions, hired thoughtfully, and delivered through a team—not only acted as its strongest individual contributor. - Software-oriented infrastructure depth. You have built and operated cloud platforms or distributed systems and can reason across infrastructure code, Kubernetes, networking, service identity, and stateful dependencies. - Safe-change and production judgment. You have owned consequential migrations and incidents, can explain failure modes and rollback limits, and know when simplifying a system is better than adding another platform. - Platform-product and engineering judgment. You understand internal customers, create interfaces other teams adopt, and make clear tradeoffs among reliability, developer autonomy, engineering effort, and workload efficiency. NICE TO HAVE - Experience with multi-tenant, cellular, regional, or dedicated enterprise infrastructure. - Familiarity with GCP/GKE, Terraform or similar IaC systems, Cloudflare, Envoy/Istio, SPIFFE/SPIRE, and managed data services. - Experience with large-fleet rightsizing, infrastructure consolidation, or migrating CI compute without disrupting developer workflows. - A track record using AI tools to increase engineering output while preserving production safeguards. Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays 🚗 Commuter Benefits (In-Office & US Only) 📱 Monthly Wellness Stipend 🧑‍💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement (In-Office Only) 🚀 Quarterly Team Gatherings ☕ In Office Amenities (In-Office Only) Want to learn more about what we are up to? - Self-driving Company https://replit.com/blog/self-driving-company - Replit Agent at Scale https://replit.com/blog/evaluating-and-improving-agent-at-scale - AI Adoption https://replit.com/blog/ai-adoption - Build Open-Source Apps https://replit.com/build/open-source-app-builder   Interviewing + Culture at Replit - Operating Principles https://blog.replit.com/operating-principles - Reasons not to work at Replit https://blog.replit.com/reasons-not-to-join-replit To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

Location: Williston, United States GoMining is one of the largest Bitcoin mining ecosystems in the world, serving millions of users globally. We run our own industrial-scale mining infrastructure across the United States — a fleet of more than 80,000 machines — and we keep expanding. We're looking for an experienced ASIC Repair Engineer who can diagnose and repair Bitcoin mining equipment at the component level, keeping that fleet running at maximum uptime. Relocation support available! We welcome candidates from across the U.S. and provide a relocation package for those moving closer to one of our data center locations. Responsibilities Diagnose and repair ASIC miners, including Bitmain and MicroBT equipment Troubleshoot and repair hashboards, control boards and power circuits at component level Diagnose chip failures, voltage irregularities and board-level defects Perform SMD and BGA soldering and component replacement Configure, test and commission repaired equipment Keep repair records, inventory updates and technical documentation Work with site technicians and site management to keep fleet uptime high Support preventive maintenance and hardware optimization Requirements 3+ years repairing Bitcoin mining equipment at component level Hands-on experience with Bitmain miners (S19 XP , S21, T21 or similar) Hands-on experience with WhatsMiner equipment (M30++, M50 series or similar) Strong understanding of ASIC miner architecture and diagnostics Practical SMD and BGA soldering skills Ability to read schematics and technical documentation Solid knowledge of electronics, circuit design and power systems Experience at a mining farm, service center or high-density data center is a strong plus Benefits Professional growth: support for courses, conferences. Paid leave: up to 20 vacation days, 15 sick days, plus holidays. Recognition programs: structured performance reviews and team awards. 401k benefits. $108,000–$240,000 per year A strong fixed base plus performance pay tied to the work you complete Our engineers average around $180,000 a year that's the middle of the team, not the top of it. With a fleet this size, the bench is always full Relocation package available

Location: Pecos, United States GoMining is one of the largest Bitcoin mining ecosystems in the world, serving millions of users globally. We run our own industrial-scale mining infrastructure across the United States — a fleet of more than 80,000 machines — and we keep expanding. We're looking for an experienced ASIC Repair Engineer who can diagnose and repair Bitcoin mining equipment at the component level, keeping that fleet running at maximum uptime. Relocation support available! We welcome candidates from across the U.S. and provide a relocation package for those moving closer to one of our data center locations. Responsibilities Diagnose and repair ASIC miners, including Bitmain and MicroBT equipment Troubleshoot and repair hashboards, control boards and power circuits at component level Diagnose chip failures, voltage irregularities and board-level defects Perform SMD and BGA soldering and component replacement Configure, test and commission repaired equipment Keep repair records, inventory updates and technical documentation Work with site technicians and site management to keep fleet uptime high Support preventive maintenance and hardware optimization Requirements 3+ years repairing Bitcoin mining equipment at component level Hands-on experience with Bitmain miners (S19 XP , S21, T21 or similar) Hands-on experience with WhatsMiner equipment (M30++, M50 series or similar) Strong understanding of ASIC miner architecture and diagnostics Practical SMD and BGA soldering skills Ability to read schematics and technical documentation Solid knowledge of electronics, circuit design and power systems Experience at a mining farm, service center or high-density data center is a strong plus Benefits Professional growth: support for courses, conferences. Paid leave: up to 20 vacation days, 15 sick days, plus holidays. Recognition programs: structured performance reviews and team awards. 401k benefits. $108,000–$240,000 per year A strong fixed base plus performance pay tied to the work you complete Our engineers average around $180,000 a year that's the middle of the team, not the top of it. With a fleet this size, the bench is always full Relocation package available

Location: Fountain Inn, United States GoMining is one of the largest Bitcoin mining ecosystems in the world, serving millions of users globally. We run our own industrial-scale mining infrastructure across the United States — a fleet of more than 80,000 machines — and we keep expanding. We're hiring a PSU Repair Engineer to diagnose and repair the power supplies that keep that fleet running. Relocation support available! We welcome candidates from across the U.S. and provide a relocation package for those moving closer to one of our data center locations. Responsibilities Diagnose and repair power supply units used in Bitmain and MicroBT mining equipment boards Perform component-level diagnostics on power supply circuits and electronic Troubleshoot IC failures, voltage irregularities, short circuits and PCB-level faults Perform SMD and BGA soldering, rework and component replacement Repair and restore power circuits, control boards and other electronic assemblies Configure, test and commission repaired equipment Keep accurate repair records, inventory information and technical documentation Work with technicians, engineers and site management to maximize fleet uptime Support preventive maintenance and equipment optimization Requirements 3+ years of hands-on component-level repair of Bitcoin mining equipment Strong experience with Bitmain power supplies, including APW11, APW12 and APW17 Hands-on experience with MicroBT WhatsMiner equipment and power supplies Strong understanding of PSU architecture, operating principles and diagnostic methods Strong SMD and BGA soldering and rework skills Ability to read schematics, board diagrams and datasheets Solid knowledge of electronics, circuit design, power electronics and electrical systems Previous experience at a mining facility , ASIC repair center or high-density data center is a significant advantage Benefits Professional growth: support for courses, conferences. Paid leave: up to 20 vacation days, 15 sick days, plus holidays. Recognition programs: structured performance reviews and team awards. 401k benefits. $108,000–$240,000 per year A strong fixed base plus performance pay tied to the work you complete Our engineers average around $180,000 a year that's the middle of the team, not the top of it. With a fleet this size, the bench is always full Relocation package available

Location: Williston, United States GoMining is one of the largest Bitcoin mining ecosystems in the world, serving millions of users globally. We run our own industrial-scale mining infrastructure across the United States — a fleet of more than 80,000 machines — and we keep expanding. We're hiring a PSU Repair Engineer to diagnose and repair the power supplies that keep that fleet running. Relocation support available! We welcome candidates from across the U.S. and provide a relocation package for those moving closer to one of our data center locations. Responsibilities Diagnose and repair power supply units used in Bitmain and MicroBT mining equipment boards Perform component-level diagnostics on power supply circuits and electronic Troubleshoot IC failures, voltage irregularities, short circuits and PCB-level faults Perform SMD and BGA soldering, rework and component replacement Repair and restore power circuits, control boards and other electronic assemblies Configure, test and commission repaired equipment Keep accurate repair records, inventory information and technical documentation Work with technicians, engineers and site management to maximize fleet uptime Support preventive maintenance and equipment optimization Requirements 3+ years of hands-on component-level repair of Bitcoin mining equipment Strong experience with Bitmain power supplies, including APW11, APW12 and APW17 Hands-on experience with MicroBT WhatsMiner equipment and power supplies Strong understanding of PSU architecture, operating principles and diagnostic methods Strong SMD and BGA soldering and rework skills Ability to read schematics, board diagrams and datasheets Solid knowledge of electronics, circuit design, power electronics and electrical systems Previous experience at a mining facility , ASIC repair center or high-density data center is a significant advantage Benefits Professional growth: support for courses, conferences. Paid leave: up to 20 vacation days, 15 sick days, plus holidays. Recognition programs: structured performance reviews and team awards. 401k benefits. $108,000–$240,000 per year A strong fixed base plus performance pay tied to the work you complete Our engineers average around $180,000 a year that's the middle of the team, not the top of it. With a fleet this size, the bench is always full Relocation package available

Location: Remote, Canada; Remote, United Kingdom; Remote, United States 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. An overview of this role We’re looking for a Principal Engineer with deep expertise in Site Reliability, Backend, or Platform Engineering to help shape the next phase of GitLab Dedicated , our fully managed single-tenant SaaS offering. This highly influential technical leadership role will set direction for how we scale a growing fleet of isolated, customer-specific environments while maintaining the reliability, security, and compliance our customers depend on. You’ll lead platform and operating-model transformation across resilience and failover, tenant orchestration, change management, self-service tooling, and platform integrations. You’ll also help align Dedicated with GitLab’s evolution toward more modular and cell-based architectures, strengthen service ownership, and establish scalable patterns that reduce operational complexity. As a Principal Engineer, you’ll influence across teams, guide complex technical decisions, mentor senior engineers, and help raise the technical maturity of the platform as we scale. What you will do Set technical direction for GitLab Dedicated, shaping architecture and platform strategy as we scale a growing fleet of isolated, single-tenant environments. Lead platform transformations across resilience, failover, tenant orchestration, change management, self-service tooling, and platform integrations. Drive scalable, modular architecture that aligns Dedicated with GitLab’s broader Cells strategy while preserving its security, isolation, and compliance requirements. Strengthen service ownership and operational maturity, helping engineering teams build, operate, and improve the production systems they own. Identify and address systemic reliability and scalability risks using production signals, incident patterns, and architectural insight. Establish reusable platform patterns and automation that reduce operational toil and allow Dedicated to scale efficiently. Lead complex technical decisions across teams, balancing reliability, security, cost, maintainability, and customer needs. Advance engineering excellence across the organization through architectural leadership, mentorship, and influence with senior engineers and engineering leaders. What you will bring Deep expertise in Site Reliability, Platform, Infrastructure, or Backend Engineering, with experience designing and operating large-scale production systems. Hands-on experience with cloud infrastructure, automation, observability, infrastructure as code, and modern production engineering practices. Strong software engineering fundamentals, with experience building production systems or infrastructure tooling in languages such as Go, Ruby, Python, or similar. Strong distributed systems and systems-design expertise, with sound judgment around reliability, failure isolation, scalability, and operational complexity. A track record of technical leadership across multiple teams, setting direction and driving complex initiatives through influence. Experience leading significant platform or infrastructure transformations, including modernization, modularization, or scaling systems through major growth. Experience leading changes that improve how engineering teams own and operate production systems, strengthening reliability, operational readiness, and accountability at scale. Exceptional technical communication and influence, with the ability to build alignment, mentor senior engineers, and guide complex architectural decisions. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $223,200 — $380,400 USD 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: Rijeka Workplace: remote CSM Rijeka is looking for self-motivated and skilled seafarers to join our expanding fleet of Columbia Shipmanagement. JOB DESCRIPTION & JOB QUALIFICATIONS Responsible for navigation safety and voyage planning, including chart corrections and publications Assists Chief Officer in cargo operations, inspections, and safety duties Responsible for the safety equipment and Voyage plan of the vessel. Holder of valid COC (STCW Reg II/1) with verification. Holder of valid STCW certifications required for the position. Good communication and leadership skills. Fluent in written and spoken English language. Experience with multicultural working environment. Safety culture and mindset.    VESSEL'S SPECIFIC REQUIREMENTS   Minimum experience requirements: 6 months in Rank with the same type/size of vessel. Experience onboard same vessel tonnage is mandatory. Experience in Steam Turbines cargo pump system is recommended. Experience with Crude Oil and STS cargo operations. Experience in trading area USA and Australia is recommended.   CONTRACT TERMS & CONDITIONS   Contract Duration [4 months +/- 1 months] Contract Benefit: Competitive salary  Terms and condition as per CBA applicable Rejoining Bonus Free Internet onboard and wellbeing support   You may include with your application any reference, specific job qualification, and your availability date.   Looking forward to welcoming you in the Columbia Group Family.