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Location: United States Keller Executive Search is partnering with a leading supply-chain services company in the utility-scale solar and renewable-energy sector to hire an Enterprise Sales Manager. Our client helps manufacturers, EPCs, IPPs, and developers manage, move, and monetize solar equipment with speed and confidence, combining a national warehousing and transportation footprint with value-added inventory, storage, and secondary-market services that keep high-stakes projects on schedule. The timing could not be stronger. The United States continues to add record volumes of new utility-scale solar capacity, and these large, high-value projects run on aggressive timelines where a single logistics failure can delay energization and strain supplier relationships. Solar modules and components are fragile, oversized, and warranty-sensitive, so buyers increasingly seek specialized partners rather than commodity brokers. This role sits precisely at that intersection, selling operational capability and reliability rather than a product on a shelf. This is a fully remote, high-autonomy hunting seat with national territory ownership. You will independently generate, qualify, and close new enterprise logistics, warehousing, and supply-chain service contracts across the solar ecosystem, then partner with operations and finance to design solutions that are both compelling to customers and profitable to deliver. It is an ideal opportunity for a consultative enterprise seller who wants to leverage an existing renewable-energy network, sell complex high-value solutions, and make a measurable revenue impact inside a fast-growing organization with strong operational and proposal support behind them. Responsibilities Develop and execute a sales strategy targeting utility-scale solar developers, EPCs, manufacturers, asset owners, and other enterprise customers Build and maintain a strong pipeline of qualified opportunities through prospecting, referrals, industry relationships, and strategic outreach Lead consultative sales conversations to understand customers’ operational, logistics, inventory, transportation, and equipment needs Develop tailored commercial proposals and solutions for complex, multi-stakeholder solar projects Manage the complete sales cycle, from initial engagement and discovery through proposal development, negotiation, and contract close Build trusted relationships with senior decision-makers and become a knowledgeable commercial partner to customers Collaborate with operations, logistics, supply-chain, and leadership teams to ensure proposed solutions are commercially viable and operationally deliverable Maintain accurate pipeline, activity, and forecasting information Monitor market activity, customer requirements, competitor developments, and emerging opportunities within the solar industry Represent the company at relevant conferences, trade shows, and industry events Support account growth by identifying additional services and opportunities within existing customer relationships Contribute market insight and customer feedback to the company’s broader growth strategy Requirements 5-7+ years of enterprise sales experience, preferably in logistics, warehousing, 3PL, renewable energy, or solar supply chains Proven success selling logistics, warehousing, 3PL, or other complex service-based solutions to enterprise customers, with evidence of personally won deals Hunter mentality with a demonstrated ability to independently generate and close net-new business, not grow an inherited book Personal ownership of consultative, multi-stakeholder enterprise sales cycles from prospecting through contract execution, engaging VP and C-level decision makers Understanding of solar or comparable capital-equipment logistics, including storage, transportation, inventory strategy, and project-based delivery models Strong business acumen across financial metrics, deal economics, and lead/lag indicators Proven ability to self-manage and stay productive in a fully remote environment with no local supervision Strong written and verbal business communication in English U.S.-based and able to cover a fully remote national territory in U.S. time zones Willingness and ability to travel nationally approximately 20 to 30% Preferred Existing, currently active relationships within solar manufacturers, EPCs, developers, IPPs, or renewable-energy supply chains Utility-scale solar experience specifically, as opposed to residential or C&I A portable, multi-segment network of manufacturer, EPC, IPP, and developer decision makers Deep solar supply-chain, warehousing, and inventory-strategy design expertise Cross-functional collaboration experience with operations, warehousing, transportation, finance, and customer success Disciplined CRM, pipeline, forecast, and proposal management (Salesforce, HubSpot, or similar) Adjacent project-cargo, heavy or oversized equipment, wind, or battery-storage logistics experience that transfers to solar Ideal Candidate Profile You are a commercially minded, self-driven enterprise hunter who thrives without an SDR team or a local office behind you. You are energized by opening new logos, running long multi-stakeholder deals across supply chain, procurement, operations, and finance, and translating complex operational challenges into tailored, margin-aware solutions. You bring credibility in the renewable-energy or logistics space, prefer selling solutions over commodities, and hold yourself to disciplined pipeline and forecast standards while building trust in person with senior buyers. Benefits Base salary range of $90,000 to $110,000, plus a commission plan on top of base Fully remote and flexible work environment and schedule PTO accrual, sick days, mental health days, and paid holidays Health, vision, dental, and life insurance 401(k) with employer match FSA/HSA options and Employee Assistance Program (EAP) Paid parental leave and wellness stipends Professional development and volunteer time off Employee discounts and referral bonuses Keller is a recruitment agency that provides services to clients ranging from startups and non profits to multinational corporations. Keller emphasizes ethical search processes, attentive candidate care, and leadership placements that support long-term client outcomes. To learn more about the firm and about our candidate services - please visit our website Equal Employment Opportunity and Non-Discrimination Policy Equal Employment Opportunity Statement: Both Keller Executive Search and our clients are Equal Opportunity Employers. 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Location: San Francisco; London; Austin; Berlin; Seattle; New York City; Toronto Workplace: Hybrid ABOUT THE ROLE The Infrastructure team builds and operates the foundational systems behind Perplexity’s products. At Perplexity, infrastructure sits on the critical path of every answer, supporting real-time search, retrieval, model serving, and agent workloads where latency, reliability, and rapid iteration directly shape the user experience. This role is for strong infrastructure engineers whose experience spans multiple domains and who are energized by cross-cutting problems that do not fit neatly within a single platform team. You do not need to be a specialist in every area. Scope ranges from owning major production systems to setting technical direction across teams, leading complex infrastructure programs, and shaping infrastructure strategy across the organization. If a specialized Cloud Infrastructure, Storage Platform, Backend Platform, Data Platform, Connector Platform, or AI Acceleration role clearly matches your expertise and interests, apply directly to it. If your experience spans several infrastructure domains or you are most energized by cross-cutting systems problems, apply here. Submit one application, and we will consider you across the Infrastructure organization. KEY RESPONSIBILITIES - Own cross-cutting infrastructure problems that span compute, storage, networking, data, deployment, and reliability, including eliminating bottlenecks across retrieval and serving paths, building shared abstractions across deployment environments, and resolving failure modes that cross platform boundaries. - Design, build, and operate distributed infrastructure supporting Perplexity’s consumer, AI, and enterprise workloads, owning systems from architecture through production operation. - Identify gaps between existing platforms and build shared abstractions, automation, and tooling that make infrastructure easier and safer to use. - Improve system performance, availability, scalability, and cost-efficiency across online request traffic and background workloads. - Debug complex production issues across service and infrastructure boundaries, then turn the findings into durable architectural improvements. - Set technical direction for complex infrastructure systems, lead high-impact programs across teams, and establish durable technical standards through collaboration with infrastructure, product, AI, and security partners. QUALIFICATIONS - 4+ years of professional software engineering experience building and operating production backend, platform, or distributed systems. - A track record of owning complex production systems end to end and delivering sustained technical impact across teams. - Demonstrated ability to set technical direction, lead through influence, and raise the engineering bar through architecture, design reviews, and mentorship. - Strong software engineering skills in Python or other systems or backend languages such as Go, Rust, C++, or Java. - Meaningful experience across at least two infrastructure domains, such as cloud platforms, distributed systems, Kubernetes, storage, databases, networking, data systems, developer infrastructure, or production reliability. - Ability to develop depth quickly in unfamiliar systems, reason across software and infrastructure layers, and drive production incidents from diagnosis through durable resolution. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco; London; Austin; Berlin; Seattle; New York City; Toronto Workplace: Hybrid ABOUT THE ROLE The Infrastructure team builds and operates the foundational systems behind Perplexity’s products. At Perplexity, infrastructure sits on the critical path of every answer, supporting real-time search, retrieval, model serving, and agent workloads where latency, reliability, and rapid iteration directly shape the user experience. This role is for strong infrastructure engineers whose experience spans multiple domains and who are energized by cross-cutting problems that do not fit neatly within a single platform team. You do not need to be a specialist in every area. Scope ranges from owning major production systems to setting technical direction across teams, leading complex infrastructure programs, and shaping infrastructure strategy across the organization. If a specialized Cloud Infrastructure, Storage Platform, Backend Platform, Data Platform, Connector Platform, or AI Acceleration role clearly matches your expertise and interests, apply directly to it. If your experience spans several infrastructure domains or you are most energized by cross-cutting systems problems, apply here. Submit one application, and we will consider you across the Infrastructure organization. KEY RESPONSIBILITIES - Own cross-cutting infrastructure problems that span compute, storage, networking, data, deployment, and reliability, including eliminating bottlenecks across retrieval and serving paths, building shared abstractions across deployment environments, and resolving failure modes that cross platform boundaries. - Design, build, and operate distributed infrastructure supporting Perplexity’s consumer, AI, and enterprise workloads, owning systems from architecture through production operation. - Identify gaps between existing platforms and build shared abstractions, automation, and tooling that make infrastructure easier and safer to use. - Improve system performance, availability, scalability, and cost-efficiency across online request traffic and background workloads. - Debug complex production issues across service and infrastructure boundaries, then turn the findings into durable architectural improvements. - Set technical direction for complex infrastructure systems, lead high-impact programs across teams, and establish durable technical standards through collaboration with infrastructure, product, AI, and security partners. QUALIFICATIONS - 4+ years of professional software engineering experience building and operating production backend, platform, or distributed systems. - A track record of owning complex production systems end to end and delivering sustained technical impact across teams. - Demonstrated ability to set technical direction, lead through influence, and raise the engineering bar through architecture, design reviews, and mentorship. - Strong software engineering skills in Python or other systems or backend languages such as Go, Rust, C++, or Java. - Meaningful experience across at least two infrastructure domains, such as cloud platforms, distributed systems, Kubernetes, storage, databases, networking, data systems, developer infrastructure, or production reliability. - Ability to develop depth quickly in unfamiliar systems, reason across software and infrastructure layers, and drive production incidents from diagnosis through durable resolution. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: 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 Procurement Operations is the front door for buying at Anthropic. We sit inside Finance Operations and own the path from “I need to buy something” to a signed agreement, an accurate purchase order, and clean spend data at month-end. We are hiring a Procurement Operations Business Partner to own that path for our research organizations and the special programs that spawn out of it. This portfolio behaves differently from the rest of the company in that it purchases goods and services from highly-specialized vendors and new programs regularly appear with real purchasing needs before any process exists for them. You will be the person who makes all of that feel simple to the researchers and program leads who depend on it, and reliable to the Finance stakeholders behind it. This is a high-volume role with an accounting core. You ensure every purchase in the portfolio is coded, dated, received, and accrued correctly, so research spend is right in the books every month. Expect a steady queue of requests, work orders, and change orders, and expect to be the person Accounting trusts on all of it. We use Claude as part of our daily workflow and are looking for someone who wants to help define what an AI-native procurement operations function looks like, including how AI changes intake, document review, vendor coordination, and requester support. Responsibilities Own the purchasing path for R&D Manage a high volume of purchase requests, work orders, and change orders each month across research teams and programs, keeping speed and accuracy high at the same time. Serve as the primary procurement partner for Anthropic's research teams and special programs, guiding requesters from initial request to signed agreement and issued purchase order. Review every purchase request in your portfolio for the things that matter downstream: the right vendor record and contracting entity, complete commercial documents, correct spend categorization and service dates, and the approvals the purchase actually needs. Determine what each request requires before it can move, whether that is a statement of work, an order form, an amendment, a security or privacy review, or a third party risk assessment, and route it to the right reviewers the first time. Launch and track contract review with Legal, keep it moving, and confirm the executed agreement supports the purchase order before it is issued. Structure purchase orders so they match how the vendor bills (fixed fee, milestone, per-unit, or usage in arrears) and how Accounting needs to see the spend, with the right GL account, cost center, and service period on every line. Manage change orders, renewals, and closures over the life of each agreement. Act as the dedicated operations partner for our research services vendor portfolio, where engagements are structured as master agreements with frequent work orders and scope changes, and where speed and documentation discipline both matter. Handle the mechanics that come with hardware, equipment, and lab purchasing, including multi line quotes, lead times, shipping and receiving, and asset handoffs. Financial completeness & accuracy Code every purchase order correctly at creation, including GL account, spend category, cost center, and service period, and understand how each choice lands in the financials (expense vs. prepaid, capitalized equipment vs. operating spend). Work the hard cases with Accounting: services that span periods, partially delivered milestones, per-unit work billed in arrears, credits and true-ups, and work orders amended mid-month. Own the open purchase order book: receipts recorded against actual delivery, periodic reviews, stale line cleanup, coding corrections, and timely closures, so PO, receipt, and invoice agree. Serve as the first line reviewer for month end accruals on your portfolio, gathering estimates from vendors and budget owners for variable spend and confirming or correcting proposed amounts so Accounting can close on time. Partner with Accounts Payable to resolve invoice holds, PO mismatches, and receiving questions so vendors are paid on time and spend lands where it belongs. Support audit and reporting requests that touch your portfolio, including commitment schedules and control evidence, with data you can stand behind. Stand up new programs Be the first procurement call when a new research program or initiative spins up. Scope what they will buy and how often, agree a right sized path with Legal, Security, and Finance, and have it working before volume arrives. Run a regular pipeline check in with your highest velocity teams so upcoming purchases are visible early and nothing urgent arrives as a surprise. Translate procurement, legal, security, and finance requirements into plain language for researchers and engineers, and carry their operating reality back to those teams so controls fit the work. Be the front door Be visible and responsive in your teams' Slack channels and office hours; answer routine purchasing questions quickly and escalate real blockers with context. Apply purchasing policy consistently and explain the why, including approval thresholds, signature authority, and when an exception is and is not available. Continuous improvement Maintain the playbooks, intake guidance, and standard operating procedures for your portfolio so the path is repeatable and does not live in one person's head. Identify manual steps, repeat questions, and failure points and fix them, including where Claude and workflow automation with AI can take work off requesters and the team. Minimum qualifications Proven track record of owning a high-volume purchasing portfolio end-to-end in procure-to-pay and intake platform. Solid working knowledge of accrual accounting as it applies to purchasing: accruals and reversals, service period and cutoff, prepaid vs. expense, and GL and cost center coding. You can explain how a purchase order becomes an entry in the general ledger. Experience supporting outsourced or managed service vendors at scale, where scope and volume move month to month and the contracts, purchase orders, and invoices have to keep up with each other. Working knowledge of how contract review, security and privacy review, and financial controls fit together in a purchase, and the judgment to know when to push a request through and when to slow it down. Preferred qualifications 5-7+ years of procurement operations, purchasing, or vendor operations, including time supporting a research, engineering, hardware, or outsourced services organization. Experience as the embedded procurement partner for a hyper scaling data operations, ML, RL, and lab environments Time at a hypergrowth technology company scaling procurement operations for outsourced or vendor delivered work. Background in accounting, accounts payable, or a month-end close process, including experience with three-way match Sourced human data, data labeling, annotation, or evaluation vendors (or comparable BPO and outsourced operations) with a point of view on where that market is heading Direct experience with Zip, Workday Financials, and Ironclad. Prior ownership of month end accrual review or open PO reconciliation for a large, variable spend portfolio Experience designing tiered intake or approval frameworks that sped up low risk purchases without weakening controls. 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: $190,000 — $230,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Canada / US / Europe Workplace: Remote turbopuffer needs someone who can close deals with engineers. Our customers are technical teams already building in a fast market. Your job is help our customers win. we’re open to two types of people: - AE who actually understands what they’re selling - technical person ready to carry a quota what you’ll do: - live in customer slack channels, helping to solve problems, drive deals forward - close inbound deals - manage POCs and work closely with solutions engineers - answer questions honestly, say no when it’s not a fit - navigate and improve internal systems must have: - technical – you can read API docs without crying - systematic – you track your pipeline and follow through - human – you don’t lie to customers - urgent – you move fast because our customers do - independent – you get things done without being explicitly told - typist - you can write well and can explain complex ideas simply - scientist - be open to experimentation and learn from your failures nice to have: - you’ve sold to developers before and know why they hate salespeople - experience with databases, search, or infra software - experience with GTM automation tools like Clay, n8n etc. - comfort with python/javascript, linux, or cloud platforms values we live by: - overstep > understep - correctness > simplicity > performance - customer traces > first principles > hunches - show > tell

Location: Costa Mesa, United States What You'Ll Do Full Cycle PCB Design: Translate system-level propulsion requirements into robust designs. Perform schematic capture and high-density PCB layouts (with a strong preference for Altium), component selection, bring-up, test, debug, and integration with the propulsion system. Engine System Electronics: Design and optimize flight controller circuits, power distribution/supplies, motor controller circuits, and electromagnetic actuator circuits. Rigorous Analysis: Conduct circuit simulations, worst-case analysis (WCA), thermal analysis, DFMEA, and component derating to ensure reliability under extreme vibration and temperature environments. Comprehensive Testing: Lead board bring-ups, Design Verification Testing (DVT), qualification (Qual) testing, and functional testing. Collaborative Design: Provide electrical support and collaborate closely with mechanical, thermal, software, test, quality, manufacturing, and systems engineering teams for development. Peer Reviews: Conduct peer-level and cross-discipline design reviews. Root Cause Analysis: Perform root cause and failure analysis in support of engine test and field operations. Required Qualifications Education & Experience: Bachelor’s Degree in Electrical Engineering (BSEE) with 5+ years of experience designing, testing, and troubleshooting complex board designs. Technical Fundamentals: Solid engineering fundamentals across Analog, Digital, and Power Electronics. Software & Tools: Deep proficiency with electronic design tools, specifically Altium Designer (or equivalent for schematic and layout) and LTSpice (or equivalent for circuit simulation). Laboratory Equipment: Competence with laboratory test equipment such as oscilloscopes, logic analyzers, thermal chambers, spectrum analyzers, function generators, DMMs, electronic loads, power supplies, and test automation. Interfaces & Protocols: Familiarity with standard interfaces (CAN, I2C, SPI, Ethernet) and common MCU/CPU architectures. Security Clearance: Eligible to obtain and maintain an active U.S. Secret security clearance. Preferred Qualifications Education: Master’s Degree in Electrical Engineering (MSEE). Advanced Tools: Experience with MATLAB / Simulink for data analysis, control loop modeling, or system simulations.

Location: Paris; Amsterdam; Linz; Munich; London; Berlin 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. THE ROLE Mistral is looking for AI Scientists with deep expertise in engineering sciences and machine learning to push the frontier of AI-accelerated simulation. Within AI4Engineering Science, you will research and train foundational physics models which are substantially more capable than what exists today and can be fine-tuned for downstream applications by both customers and internal teams. You will work across the full research stack: curating high-fidelity simulation datasets, designing and training novel model architectures, and rigorously evaluating them against real engineering validation standards. Working closely with the broader research organization, you'll ensure the foundation models you build are general enough to become the backbone of many downstream products, not just a single point solution. This role builds on a strong, world-class foundation, and the goal is to take it further. You'll work one vertical at a time toward foundation models that genuinely transfer and fine-tune across engineering tasks, with high-quality simulation data pipelines, physics-based evaluation, and uncertainty / out-of-distribution estimation as first-class concerns. There's no inherited playbook for most of what's left to do: you'll help define the architectures, training strategies, and validation standards the team builds on, not just extend an existing one. WHAT YOU WILL DO - Research and train novel foundation models for physics simulation, pushing past today's state of the art in accuracy, generalization, and scale - Design and run large-scale simulation campaigns using domain-specific solvers to build the high-fidelity datasets foundational physics models need - Investigate architectures and training strategies (e.g. multi-fidelity training, pretraining objectives, scaling behavior) that let a single foundation model transfer and fine-tune well across diverse engineering tasks - Rigorously evaluate model coverage, accuracy, and robustness against industry validation standards, and diagnose failure modes arising from data gaps or architecture limitations - Stay on top of the latest developments in the scientific community and contribute to Mistral's standing at the frontier of AI-for-engineering research WHAT WE'RE LOOKING FOR - PhD or Master's in CS/AI or an engineering science: Mechanical Engineering, Electrical Engineering, Computational Fluid Dynamics, Structural Mechanics, EDA, Semiconductor Engineering, or a related field - Strong, hands-on machine learning expertise with a deep understanding of model architectures, training dynamics, and evaluation methodology is core to this role - You have developed ML methods for simulation or surrogate modelling - You write clean, readable Python code and are comfortable in Linux/HPC environments - Fluent English with excellent communication skills, able to explain technical simulation and ML concepts to both engineering and non-technical audiences - Self-directed, you don't need detailed roadmaps to make progress - Low-ego, collaborative, and eager to learn at the intersection of simulation and ML - Demonstrated success through industrial projects, academic work, or personal projects IT WOULD BE GREAT IF YOU - Have industrial or academic experience with simulation solvers (e.g. OpenFOAM, LS-DYNA, ANSYS, COMSOL, Abaqus, Fluent, STAR-CCM+, PowerFlow, NekRS, Tau/CODA, JAX-Fluids, or equivalent; Cadence/Synopsys/Siemens EDA or equivalent) - Have experience automating large-scale simulation campaigns on HPC clusters - Have contributed to a large open-source or industry codebase - Have publications in engineering or ML venues (AIAA, ASME, JFM, NeurIPS, ICLR, etc.) 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: Paris; Palo Alto; Amsterdam; Linz; Munich; London; Berlin Workplace: Hybrid 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. THE TEAM You will join the AI4Engineering Science team, the Mistral research group that builds the data and evaluation infrastructure and owns the SFT/RL processes for AI4Engineering that teach our frontier LLMs to do real engineering work. The agentic engineering group works alongside the Physics AI research in the wider Science organisation. This seat sits in the agentic CAD stream. Together with the Solutions and Applied teams, the group carries this work into customer projects with industrial partners in automotive, aerospace, semiconductors, and beyond. THE ROLE Mistral is looking for an AI Scientist with deep machine learning expertise and hands-on CAD experience to expand what our agentic tools can do for computer-aided design. Your focus is a single mission: teaching Mistral's LLMs to generate, analyze, and modify CAD designs the way an expert design engineer would. Your core work is building the pre- and post-training data for Mistral's LLMs to reason about and execute real CAD tasks: text-to-CAD and image-to-CAD generation from technical drawings, geometric analysis and QA of CAD parts, and modification of existing designs. Because Mistral trains its own frontier LLMs, the data and verifiers you design ship directly into models you can hold - a rare position, and the core of the job. Alongside this, you will help shape the agent architectures and harnesses that let these models operate reliably inside multi-step CAD workflows, driving CAD tools through APIs or computer use across the whole design loop. This is early-stage work, and that's the point: you are joining at the foundation, shaping the data, verifiers, and agent scaffolding that decide whether these systems become reliable or stay demo-grade. There is no inherited playbook; you will help define what good looks like, and your work will set the direction the CAD stream builds on rather than extend an existing one. WHAT YOU WILL DO - Design pretraining, SFT, and RL data for CAD tasks: text-to-CAD and image-to-CAD generation from technical drawings, geometric analysis and QA of CAD parts, and design modification - Define verifiers and evaluation criteria that capture what "correct" and "high-quality" actually mean for CAD tasks - Scale the data pipelines that produce agentic CAD training traces - Design and improve agent architectures and harnesses: how models plan, call CAD tools via API or computer use, recover from errors, and chain steps together across long-horizon design workflows - Build and maintain CAD evaluation benchmarks and diagnostic tooling, from parametric CAD and drawing-to-3D benchmarks to industrial evaluations, identifying where models fail and tracing those failures back to gaps in data, reward design, or agent scaffolding - Collaborate with CAD domain experts and the CAE and EDA streams (and the science and solutions teams more broadly) to identify which CAD workflows are highest-value to target next - Contribute to Mistral's broader pre- and post-training research, sharing findings and methodology across the science organization WHAT WE'RE LOOKING FOR - Deep, hands-on machine learning expertise, particularly LLM development: you have built LLM training pipelines (SFT, RL, fine-tuning, GRPO), demonstrated in publications or shipped systems rather than CV claims - Demonstrated hands-on CAD experience: you have designed, scripted, or automated real CAD workflows in tools such as SolidWorks, CATIA, Siemens NX, FreeCAD, or CADQuery, ideally with CAD-kernel grounding (OpenCASCADE, build123d) - Fluent English with excellent communication skills: you can explain technical ML and CAD concepts to both engineering and non-technical audiences - You write clean, readable Python code and are comfortable in Linux/HPC environments - Self-directed: you do not need detailed roadmaps to make progress - Low-ego, collaborative, and eager to learn at the intersection of CAD and ML It would be great if you: - Have experience building or fine-tuning agentic systems (tool use, multi-step planning, agent orchestration frameworks) - Have experience with reward modeling, RLHF/RLAIF/RLVR, or preference-based training - Have first-author publications or open-source benchmark work in agentic CAD or CAD-ML, such as CAD generation benchmarks or RL/GRPO fine-tuning of vision-language models for CAD - Have contributed to a large open-source or industry codebase - Have publications in engineering and ML venues (NeurIPS, ICLR, ICCV, SIGGRAPH, JFM, AIAA, etc.) 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: Paris; Amsterdam; Singapore; London; Lausanne Workplace: Hybrid 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. ROLE SUMMARY As a Research Engineer on Forge, you will turn real customer requirements into reliable training and deployment workflows. You’ll work end‑to‑end across model adaptation and post‑training (CPT/SFT/RL/distillation), evaluation, data, and infrastructure. The role bridges research experimentation and production constraints. This role sits in Applied Science, with direct impact on client outcomes. You’ll collaborate closely with scientists, engineers, product, and customer‑facing teams to ensure Forge projects ship, are maintainable, and can be trusted by others. Interview focus can vary (algorithms, infrastructure, evals, or data). You don’t need to match every bullet below to apply. WHAT YOU WILL DO - Build and improve post‑training and evaluation workflows (CPT/SFT/RL/distillation), turning prototypes into repeatable Forge “recipes”. - Develop tools and pipelines for synthetic data generation, data curation, training, evaluation, and deployment. - Debug and harden large‑scale ML systems: distributed training, scheduling/execution, checkpointing, observability, and reproducibility. - Improve the Forge codebase via clear APIs, tests, documentation, and maintainable abstractions. - Push the frontier of our RL training stack (e.g., high-throughput async rollout and scalable post‑training systems at frontier-model scale) - Make sure Forge deployment is seamless and adaptable to a diversity of clients (hardware access, software stack, cloud and on-premises, …) - Partner with researchers and infrastructure engineers to translate bottlenecks into concrete system improvements. ABOUT YOU - Strong Python engineering skills and experience working in large codebases (testing, code review, CI, operational ownership). - Hands‑on experience with PyTorch, JAX, or similar. - Strong systems and infrastructure fundamentals. - Experience with LLM training or post‑training: fine‑tuning, RL, distillation, evaluation, and/or data pipelines. - Excellent debugging skills in ambiguous systems (distributed jobs, data issues, quality regressions, infra failures). - Clear communication with technical and non‑technical stakeholders. - High agency, low ego, and comfort in fast‑moving, under‑specified environments. NICE TO HAVE - Distributed training experience (FSDP, DeepSpeed, Megatron, etc.). - Cluster/orchestration experience (SLURM, Ray, Kubernetes, Kueue, Karpenter, Skypilot, etc.). - Experience building reliable ML infrastructure, evaluation systems, or large‑scale data processing pipelines. - Research experience in LLMs, agents, multimodal models, reasoning, code, or domain adaptation. - Open‑source contributions, publications, or widely used internal tooling. - Experience training multi‑billion‑parameter models (pre‑training or RL). Experience training on petabyte- and exabyte-scale datasets. - Ability to identify bottlenecks across the stack and drive improvements from first principles. 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: Hong Kong & Sydney Location: Hong Kong and Sydney Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager operating across all liquid asset classes worldwide. We are a technology- and data-driven organisation applying a scientific approach to investing. By combining data, research, technology and trading expertise, we foster a collaborative environment that enables us to solve complex challenges. Our culture of innovation drives our ambition to deliver high-quality returns for our investors. Your future role at QRT We are looking for an experienced Trading Systems Software Engineer to help build the applications, platforms and engineering capabilities that support QRT’s global trading environment. This is a broad software engineering role spanning application development, distributed systems, cloud technology, deployment automation and production engineering. You will design and build software used by traders, quantitative researchers, operations teams and other engineers across the firm. The focus extends beyond delivering individual features. You will identify opportunities to create scalable, reusable capabilities that improve how trading systems are developed, deployed, monitored and operated across multiple teams and trading desks. Working closely with both technical and business stakeholders, you will gain a detailed understanding of trading workflows and translate complex requirements into reliable, maintainable and well-designed software. What you’ll do Design, develop and maintain production-grade applications, services and APIs supporting QRT’s trading platform. Build shared platforms and reusable capabilities that can be adopted across multiple trading desks and engineering teams. Develop modern web applications and operational tools that improve visibility, control and efficiency across trading workflows. Design scalable distributed and event-driven systems that integrate with trading platforms, market data services and internal infrastructure. Build deployment tooling, release automation and self-service capabilities that make software easier and safer to deploy and operate. Develop automated workflows for data processing, operational tasks and engineering processes using technologies such as Apache Airflow. Partner with traders, quantitative researchers and operations teams to understand their needs and solve practical business problems. Design software for latency-sensitive environments, balancing performance with reliability, scalability and operational simplicity. Build observable and resilient systems with appropriate monitoring, alerting, recovery and failure-handling capabilities. Work alongside infrastructure, cloud and DevOps engineers to deploy and support software across global production environments. Contribute to technical design and architectural decisions, evaluating new technologies where they can deliver meaningful value. Take ownership of software throughout its lifecycle, from initial design and implementation through to production support and continuous improvement. Your present skillset You will likely have: At least five years of experience developing and supporting production-grade software. Strong programming and software engineering skills in one or more languages such as Python, Java, Go, Node.js or C++. Experience designing maintainable, testable and scalable applications and services. A strong understanding of software design principles, data structures, algorithms and engineering fundamentals. Experience building RESTful APIs, distributed systems or event-driven architectures. A good working knowledge of Linux environments. Experience working with relational databases such as PostgreSQL or MySQL. Exposure to containerisation, orchestration and delivery technologies such as Docker, Kubernetes and CI/CD pipelines. Experience with public cloud technologies, preferably AWS. An understanding of messaging technologies such as Kafka or RabbitMQ. Experience considering reliability, observability, performance and failure recovery when designing production systems. Strong analytical and problem-solving skills, with the ability to make sound engineering decisions and explain the associated trade-offs. The ability to work effectively with both technical and non-technical stakeholders. Experience in one or more of the following areas would be advantageous: Apache Airflow or a comparable workflow-orchestration platform. React, Vue, Angular or another modern front-end framework. Deployment automation, developer platforms or operational tooling. Market data, order management systems, execution management systems or electronic trading platforms. Financial markets or another complex, time-sensitive production environment. You do not need to have worked in financial services. We are interested in engineers who are curious, technically strong and motivated to understand how technology supports a global trading business. Your way of working You will thrive in this role if you: Enjoy designing systems as well as implementing them. Think about scalability, reliability and maintainability from the outset. Look for opportunities to automate repetitive work and improve engineering processes. Take ownership and remain accountable for the quality of your software in production. Work collaboratively and seek to understand the needs of the people using the systems you build. Approach technical decisions pragmatically and can balance competing business and engineering priorities. Are intellectually curious and enjoy learning about unfamiliar technologies and business domains. Maintain high standards while remaining open to feedback and different perspectives. Why join QRT? Technology sits at the heart of QRT. You will work alongside talented traders, quantitative researchers and engineers, building software that directly supports our global trading activities. The role offers exposure to a broad range of engineering challenges, from cloud-native services and distributed systems to trading applications, deployment platforms and operational tooling. You will have the autonomy to shape solutions, contribute to architectural direction and see your work used every day by teams across the firm. If you enjoy building scalable systems and creating software that makes engineers, traders and operational teams more effective, you will have the opportunity to make a meaningful impact at QRT.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We believe powerful AI can compress a century of scientific progress into a decade. Claude Science is a big part of building toward that future. Claude Science is an AI workbench that gives researchers a single environment for work that today spans dozens of disconnected tools — literature, specialized databases, scientific computing, analysis, and publication-ready outputs. Claude Science already renders protein structures, genome tracks, and chemical structures natively, and coordinates multi-agent workflows with built-in review for citation and calculation errors — and we’re just getting started. Much of this is being built 0→1 right now: you’ll shape both the product and the architecture in a category no one has defined yet. You'll be a technical leader who thinks holistically about the end-to-end researcher experience, partners directly with our internal research team to push model capabilities into production, and carries real ownership over what we ship next. Our north star is accelerating scientific progress — across biology, chemistry, physics, and beyond — from early discovery through real-world application, by an order of magnitude. This work supports programs like Anthropic’s AI for Science Program and our rare disease research grants . What you'll do Ship fast against a roadmap you help shape: this is a product in a category no one has defined yet, and the highest-leverage problems are still unclaimed Interface directly with working scientists — academic labs, industry R&D teams, and research institutes — during key conversations, translating what you learn into engineering priorities Partner with product and design to turn how scientists actually work — from hypothesis to analysis to publication — into shipped product Work closely with research to make the models better at science: shaping evals, surfacing failure modes, and feeding what users hit in the real world back into model development You may be a good fit if you Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level Have built products from 0 to 1 in fast-moving environments, and can set technical direction with limited precedent to lean on Have built AI products and know what it takes to turn model capabilities into applications people actually use Are comfortable working directly with technical domain experts and translating what you learn Drive cross-team alignment to ship impactful work, with influence over authority Strong candidates may also have Background in chemistry, biology, physics, or another science Experience working with research teams to improve domain-specific model capabilities, including evaluation frameworks 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: $405,000 — $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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York, NY (HQ); San Francisco, CA Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE We’re looking for a Senior Business Systems Engineer to own and evolve Ramp’s Quote-to-Cash systems. You’ll build and maintain Ramp’s Salesforce-based quoting platform, contract workflows, and Billing/Core integrations that turn complex commercial agreements into accurate, supportable customer outcomes—from quote creation and approvals through order forms, provisioning, billing, renewals, and amendments. This is not a Salesforce CPQ implementation role. Ramp uses an in-house Quote-to-Cash platform built on Salesforce, so we’re looking for a strong Salesforce engineer with experience in quoting, pricing, contracts, billing, subscriptions, or other complex commercial workflows. This role sits in Growth Engineering’s Business Systems Engineering team and partners closely with Deal Desk, Legal, Finance, Billing Engineering, Product, and GTM teams. You’ll combine hands-on Salesforce engineering with systems design and strong commercial judgment to make high-stakes revenue workflows reliable, scalable, and easier for teams to use.     WHAT YOU’LL DO - Design, develop, test, and deploy applications on the Salesforce Platform. - Design, build, and operate Ramp’s Salesforce-based Quote-to-Cash platform and the integrations between Salesforce, Ironclad, Billing/Core, and adjacent business systems. Own data contracts, idempotency, error handling, reconciliation, and safe lifecycle changes for quotes, contracts, and subscriptions. - Design, develop, and maintain integration solutions using in-house services and approved automation platforms. - Drive architecture, tooling, and design decisions that keep commercial systems fast, reliable, and scalable. - Write and communicate technical specifications, including architecture diagrams, data models, process flows, and sequence diagrams. - Own data integrity and the operating assumptions for your domain; continually improve them. - Partner with the rest of the team on code reviews, operational support, debugging, and solution design. WHAT YOU’LL NEED - 7+ years building applications on the Salesforce Platform. - 5+ years of systems architecture and integration experience. - Strong hands-on experience with Apex, triggers, Lightning Web Components, Flows, and asynchronous processing. - Working knowledge of another programming language, such as Python. - Strong API and integration-design skills, including reliable handling of retries, duplicate events, partial failures, and data reconciliation. - Experience with Quote-to-Cash domains such as quoting, pricing, approvals, contract lifecycle management, billing, subscriptions, renewals, or amendments. Experience with Salesforce CPQ is welcome but not required. - Familiarity with the broader GTM stack beyond Salesforce, such as Gong, LeanData, contract lifecycle management, billing, or revenue systems. - Strong knowledge of synchronous and asynchronous integration patterns, streaming APIs, and publish/subscribe architectures. - Working knowledge of data pipelines, CI/CD, Salesforce platform limits, code coverage, and unit-testing practices. - Excellent written and verbal communication skills, including the ability to translate complex commercial requirements into simple, durable system behavior with non-engineering partners. - Experience using AI-assisted development tools thoughtfully and evaluating their output. NICE TO HAVES - Snowflake/DBT - Kafka experience - Experience with Agile methodologies BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: Bangalore, India 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 are looking for a Senior Release Engineer to help design, standardize, and operate reliable enterprise application delivery across the Enterprise Technology & AI team. This role will establish scalable CI/CD practices for business-critical platforms such as Salesforce, Zuora and other Business Systems while enabling engineering teams to ship changes safely, quickly, and with clear operational controls. The ideal candidate combines strong release engineering and automation skills with practical experience supporting enterprise SaaS applications. You will build and maintain GitLab CI/CD or comparable CI/CD pipelines, develop reusable scripts and deployment tooling, improve release governance, and partner with application, security, compliance, and business teams across the release lifecycle. Daily use of approved AI-assisted engineering tools, including Claude, Duo Agent Platform or comparable enterprise-approved tools, is a mandatory expectation for DevOps, troubleshooting, documentation, testing, and automation activities. What you'll do Design, build, and maintain GitLab CI/CD or comparable CI/CD pipelines for enterprise applications, including validation, testing, packaging, deployment, promotion, rollback, and post-release verification. Develop reusable automation using scripting languages such as Python to reduce manual release activities and improve repeatability. Use approved AI-assisted engineering tools such as Claude or similar tools every day to accelerate pipeline development, scripting, test creation, troubleshooting, documentation, release analysis, and operational automation. Define and implement CI/CD patterns for platforms such as Salesforce, Zuora, and other Business Systems. Establish environment and promotion strategies across development, test, staging, and production, including configuration management and deployment sequencing. Implement quality gates, automated checks, approvals, audit trails, and policy controls appropriate for enterprise application releases. Partner with application owners and development teams to define branching, versioning, release cadence, and rollback standards. Improve release observability through deployment dashboards, pipeline metrics, change records, notifications, and operational reporting. Investigate failed deployments and release issues, lead root-cause analysis, and implement durable corrective actions. Contribute to release calendars, change planning, blackout-period coordination, and risk-based release decision-making. Build documentation, runbooks, reusable templates, and enablement materials so teams can adopt consistent delivery practices. Coach engineers and application teams on GitLab CI/CD or comparable CI/CD tools, release automation, trunk/branching strategies, testing, and operational readiness. Collaborate with security, compliance, architecture, and enterprise application stakeholders to meet control requirements without creating unnecessary delivery friction. What you'll bring Bachelor’s degree in Computer Science,Information Systems, or equivalent practical experience. 7+ years of experience in release engineering, DevOps or a related discipline. Experience in Release & deployments for enterprise SaaS applications such as Salesforce, Zuora or Business Systems. Strong hands-on experience designing and operating GitLab CI/CD or comparable CI/CD pipelines in production environments. Proficiency in at least one scripting language, such as Python, with the ability to write maintainable automation and integrations. Mandatory hands-on experience using AI-assisted development and automation tools such as Claude or comparable enterprise-approved tools as part of day-to-day DevOps and release engineering work. Experience with source control, branching and merging strategies, artifact management, automated testing, deployment orchestration, and rollback practices. Working knowledge of REST APIs, webhooks, JSON, authentication patterns, and integration troubleshooting. Experience managing releases across multiple environments with strong attention to configuration, dependencies, access controls, and auditability. Demonstrated ability to troubleshoot pipeline failures, deployment issues, integration defects, and environment inconsistencies. Strong communication and collaboration skills, with the ability to work effectively across engineering, business, security, compliance, and operations teams. Enterprise application releases become more predictable, repeatable, and transparent. Manual deployment effort and avoidable release errors decrease through automation and standardization. About the team ETA teams adopt reusable GitLab CI/CD or comparable CI/CD patterns for Salesforce, Zuora, and other enterprise platforms.Release quality improves through automated validation, testing, policy checks, and post-deployment verification. Deployment, change, and compliance evidence is available through reliable pipeline records and operational reporting. Application teams can move faster while maintaining appropriate controls for business-critical systems. AI-assisted DevOps adoption measurably improves engineering throughput, troubleshooting speed, automation coverage, and documentation quality without reducing delivery controls. 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: Remote (Canada) Workplace: Remote BUILD SOMETHING PEOPLE LOVE Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $169 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. We're proud of what we've built — and we're just getting started. Read our Culture Manual https://www.wealthsimple.com/en-ca/culture and learn more about how we work https://www.wealthsimple.com/en-ca/careers. ABOUT THE ROLE We’re looking for a Staff Product Manager to own Wealthsimple’s Connectivity Platform, spanning two critical areas: - Brokerage & Bank Linking: How clients securely and reliably connect external financial institutions to Wealthsimple. - Public API: How clients and partners securely access and use Wealthsimple financial data outside of Wealthsimple. Together, these capabilities define how Wealthsimple connects to the broader financial ecosystem, and how every product team inside Wealthsimple builds on the external financial data that flows through it. This role will set the strategy for that platform and turn it into a reliable, scalable and differentiated capability for our clients, our product teams and our partners. This is a platform role with a meaningful client experience surface. You’ll need to be equally comfortable thinking about APIs, data models and platform architecture as you are designing a client UX or deciding how Wealthsimple should work with an external provider. ABOUT THE TEAM The Brokerage & Bank Linking team builds the technology that lets clients link their outside bank and brokerage accounts to Wealthsimple. It owns the automated and manual linking experiences end to end, along with the three connectors behind them: Plaid, Flinks, and WST, our own in-house connector. That makes it one of the highest leverage surfaces in the company, and powers a growing set of experiences built by other product teams. WHAT YOU’LL OWN Connectivity Strategy - Set the long term vision and strategy for how Wealthsimple connects with the broader financial ecosystem. - Define the capabilities we should build ourselves, where we should rely on partners, and where we can create differentiated client value. - Develop a roadmap that balances immediate product needs with investments in reusable platform capabilities. Brokerage & Bank Linking - Own the end to end experience for connecting external bank and brokerage accounts to Wealthsimple — automated and manual, including how clients recover when an automated connection fails. - Improve connection success, reliability and coverage across institutions, and own the routing strategy that decides which connector handles which institution and flow. - Own the client experience, including institution selection, authentication, errors, recovery and connection management. - Drive reliability and AI Powered self-healing so connections detect and recover from failure without manual intervention. - Balance conversion against fraud exposure and operational load, making those tradeoffs deliberately with our risk and operations partners. - Develop the platform capabilities that allow Wealthsimple products to consume external financial data consistently. - Own relationships and product integrations with connectivity vendors such as Plaid and Flinks, and decide where our own connector should lead — including how much of the connector business Wealthsimple should be in long term and where it makes more sense to partner. Public API - Own the strategy and roadmap for Wealthsimple’s Public API and external data connectivity. - Make it safe and easy for clients to permission their Wealthsimple financial data to the products and services they choose. - Define the platform capabilities required for authentication, consent, permissions, data access and partner integrations. - Identify and prioritize the partners and use cases that matter most to Wealthsimple clients. - Build toward a world where Wealthsimple is the financial institution where clients have the most control over their financial data. - Accelerate wealthsimple and our industry toward open banking. SKILLS YOU BRING You’re a strong product thinker who can operate across platform infrastructure, external ecosystems and client experience. You likely have: - Experience owning a platform, API, developer product or integrations platform, with a track record on metric-attached outcomes like conversion, success rate or reliability — not only feature delivery. - Enough technical depth to work closely with engineers on APIs, authentication, data models, routing and platform architecture. - Experience delivering through external vendors or partners whose roadmaps you don’t control, including making thoughtful build versus buy decisions and holding vendors accountable for product outcomes. - Comfort treating reliability as product work — error taxonomies, failure recovery, observability, and the operational load a product creates. - Experience weighing growth against fraud, risk and compliance, and holding both sides of that tradeoff. - The ability to turn a collection of technical capabilities into a clear product strategy and compelling long term vision, and to make the case for investing in it. - Strong analytical instincts and comfort using data to understand reliability, conversion, coverage and product performance, including building the measurement where it doesn’t exist yet. - Excellent cross functional leadership across Engineering, Design, Security, Legal, Compliance, Operations and external partners. - A bias toward simplifying complicated systems rather than layering more complexity on top of them. NICE TO HAVES - Experience with open banking, Canada’s consumer-driven banking framework, or building to a data sharing standard - A background in financial data aggregation, whether at an aggregator, a bank, or a fintech consuming one - Experience shipping a public API or developer platform as a commercial product, including partner onboarding and support WHAT GREAT LOOKS LIKE You won’t just operate Bank Linking and ship API endpoints. You’ll create a coherent connectivity strategy for Wealthsimple: making it easier for clients to bring their financial life to Wealthsimple, easier to move their financial data where they want it to go, easier for any team at Wealthsimple to build on that data, and increasingly less dependent on the slow pace of connectivity innovation from incumbent financial institutions. You’ll also have made the case for what this platform should become — the metrics, the roadmap and the investment argument that get it there. WHY WEALTHSIMPLE? 🌸 Top-tier health benefits and life insurance 📈 Long-term group savings with employer match, through Wealthsimple for Business 🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year* ✈️ 90 days away: work outside Canada for up to 90 days per year* 👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS 🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work. *Unlimited paid sick days, Wellness Days and the 90 day away program do not apply to certain roles. ICYMI Technology & Innovation at Wealthsimple: We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building. Inclusion Statement: We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status. Accessibility Statement: We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know — we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs. AI in Hiring: We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.

Location: Palo Alto Workplace: Hybrid 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. THE ROLE This role focuses on building and operating the ML platform that powers large-scale training, evaluation, and batch inference at Mistral AI. You will develop the infrastructure that enables researchers and engineers to run distributed GPU workloads reliably across clusters, hardware types, and regions. You will work across the full ML lifecycle, from workload scheduling and capacity management to platform APIs, observability, and production operations. You will take ownership of critical systems and help turn complex infrastructure into reliable, self-service capabilities. WHAT YOU WILL DO - Build the ML Platform: Develop services, APIs, controllers, and tooling for training, evaluation, fine-tuning, and batch inference. - Orchestrate GPU Workloads: Build systems for queueing, admission control, quotas, priorities, preemption, and topology-aware placement. - Manage Compute Capacity: Improve how heterogeneous GPU resources are provisioned, allocated, and utilized across clusters. - Enable Multi-Cluster Execution: Place workloads based on capacity, data locality, hardware requirements, and organizational priorities. - Improve Researcher Experience: Create self-service workflows that make distributed workloads easy to launch, observe, debug, and reproduce. - Optimize Performance: Improve GPU utilization, scheduling latency, workload startup time, throughput, and infrastructure efficiency. - Build for Reliability: Develop observability, failure recovery, capacity planning, and operational tooling for critical ML workloads. - Operate What You Build: Participate in on-call rotations and troubleshoot issues across applications, schedulers, networking, storage, and GPU infrastructure. WHAT WE'RE LOOKING FOR - Have 4+ years of experience in ML infrastructure, distributed systems, Kubernetes platform engineering, or a related field. - Are proficient in Python or Go and comfortable working with production-grade distributed systems. - Have strong Kubernetes knowledge, including controllers, operators, CRDs, scheduling, networking, storage, and resource management. - Understand technologies such as Kueue, Karpenter, Volcano, and Kyverno, and the problems they address in workload scheduling, provisioning, and policy enforcement. - Understand distributed ML workloads, including training, fine-tuning, evaluation, checkpointing, and batch inference. - Are familiar with GPU infrastructure and technologies such as PyTorch, CUDA, NCCL, and high-performance networking. - Understand concepts such as quotas, priorities, preemption, gang scheduling, topology awareness, and workload admission. - Can diagnose performance and reliability problems across software, orchestration, networking, storage, and hardware. - Care about developer experience and enjoy turning complex infrastructure into simple, reliable interfaces. - Thrive in an ambiguous, fast-moving environment shaped by frontier AI research. 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: Malta As a Platform Engineering Tech Lead , you will provide hands-on technical leadership for a team responsible for building and operating cloud and platform capabilities that power our applications and customer experiences. Your primary focus will be AWS, cloud, edge and platform technologies , while working closely with other Platform Engineering specialists, including our Kubernetes Tech Lead. You will help shape technical solutions, work with Architects, build POCs, review implementations and get hands-on with the technology when needed. This is a role for someone who enjoys being close to the technology while also helping engineers solve complex problems, raising engineering standards and driving the platform forward. A taster of what you will be involved with Provide hands-on technical leadership – Shape technical solutions with Architects, define technical approaches, conduct POCs and drive engineering standards across cloud, edge and platform technologies. Build and enable the team – Coach and unblock engineers, share knowledge and promote collaboration so that knowledge is distributed and no single person becomes a point of failure. Support technical assessments and code reviews. Drive reliability and operational excellence – Lead technical incident response and RCA, ensuring solutions are production-ready, resilient and have appropriate rollback strategies. Observability as a first-class concern – including logs, metrics, traces and SLOs. Drive cloud and platform evolution – Build and improve AWS-based capabilities through automation, Infrastructure as Code and modern platform engineering practices, while identifying opportunities for innovation and modernisation. Collaborate across Platform Engineering – Work closely with Kubernetes, Observability, Delivery, Security and Architecture teams to ensure our platform operates as a cohesive ecosystem. What we’re looking for Strong experience in AWS and cloud engineering in production environments. Experience with AWS edge and networking technologies, such as CloudFront, Route 53, WAF, load balancing, CDN and edge computing. Good working knowledge of Kubernetes and containerised platforms and the ability to work effectively alongside Kubernetes specialists. Strong experience with Infrastructure as Code and automation, particularly Terraform and Ansible, along with modern CI/CD practices. Comfortable remaining hands-on with code, infrastructure, configuration and troubleshooting. Experience with code reviews, technical design discussions and POCs. Strong understanding of observability and reliability, including logs, metrics, traces and SLOs. Experience mentoring engineers and providing technical leadership without relying on formal management authority. Strong communication skills and the ability to clearly explain technical decisions, trade-offs and risks. Who We Are Betsson Group is one of the largest companies within the Global iGaming space and can trace our heritage as far back as the 1960’s. We’re Swedish and publicly listed too with our Operational HQ located on the Mediterranean Island of Malta. We strive to deliver the best customer experience in the industry. As a market leader within iGaming we offer online gaming products across 12+ jurisdictions and 20+ brands. You will be part of a passionate team, which is building an industry leading, scalable, multi-brand platform used by hundreds of thousands of our customers! Product Development at Betsson Group Our Product Development organisation is truly Global with cross functional teams spanning 6 Tech Hubs – Malta, Budapest, Stockholm, Tallinn, Malaga and Athens. With around 1,000 strong professionals, the Product Development organisation is spear-headed by our CTO-CPO with all our talented Area Teams working together. Challenge accepted? By submitting your application, you understand that your personal data will be processed as set out in our Privacy Policy

Location: Beograd, Serbia Workplace: hybrid ABOUT THE ROLE We are looking for forward-thinking, high-performing AI Engineers who are excited to pioneer the future of AI-driven engineering at Paysend. In this role, you will work hands-on with Claude Code and the Anthropic API to design, harden, and ship agentic systems that write, review, test, and deploy code. This is a high-impact, build-and-own opportunity: you will take cutting-edge AI prototypes and turn them into resilient production infrastructure - directly empowering our global engineering teams, accelerating our product velocity, and helping us solidify Paysend as the definitive end-to-end payment infrastructure for the modern world. THE ENGINEERING PROBLEM The problem is not to make an LLM generate code. The problem is to make AI-assisted and agentic software delivery reliable enough to become part of normal engineering work. These systems operate inside real software delivery workflows. They need to deal with incomplete context, failed execution, incorrect assumptions, external dependencies, changing repository state, and cases where an agent should not continue on its own. This means designing clear execution boundaries, decision points, observability, recovery and escalation paths, not only the agent behaviour itself. The role includes shaping how these systems work, not only implementing integrations with existing AI tools. WHAT YOU'LL DO Design end-to-end AI-assisted delivery workflows, including agent responsibilities, execution boundaries, decision points, human intervention, failure handling, recovery, and escalation Design and refine AI-driven pipelines that automate coding, code review, testing, and deployment tasks Build and optimise agentic workflows using Claude Code and the Anthropic API, including custom tooling, MCP server integrations, sub-agents, and stateful orchestration logic Engineer robust prompts, benchmark suites, and automated eval datasets; measure and improve pipeline accuracy, latency, and API costs Define workflow-specific success criteria and operational evidence, including correctness, reliability, intervention and escalation rates, failure modes, and recovery effectiveness Integrate core Anthropic capabilities (tool use, structured outputs, prompt caching, batch processing) into internal developer platforms Handle unglamorous production work: sandboxed execution, strict error handling, retries, observability, guardrails, and edge cases Own these systems after initial implementation: observe how they behave in real engineering workflows, investigate failures and incorrect behaviour, and improve the system based on operational evidence Partner with engineers across the org to identify automation opportunities and roll out agentic tools safely with human-in-the-loop review mechanisms WHAT WE'RE LOOKING FOR Strong software engineering background, with experience designing, building, and operating production systems, and strong hands-on experience with Python or TypeScript Ability to decompose end-to-end engineering workflows, identify decision boundaries, failure modes, dependencies, observability needs, and recovery paths Direct, hands-on experience with Claude Code—you've used it beyond casual experimentation and understand its strengths, limits, and configuration (CLAUDE.md, sub-agents, hooks) Experience building with LLM APIs: prompt engineering, tool/function calling, structured outputs, context window optimization, agentic loops, and evaluation Familiarity with MCP (Model Context Protocol) server integration and custom workflows Comfort turning prototypes into production systems: CI/CD integration, containerized execution, reliability engineering, and monitoring Pragmatic judgment about where AI automation helps and where traditional deterministic logic or human oversight is required NICE TO HAVE Experience with agent orchestration frameworks or building custom agent harnesses/tooling Track record shipping internal developer platforms or CLI tooling Contributions to open-source AI frameworks, developer tools, or MCP servers Why Join Paysend? Make a Global Impact: Join a company that is transforming how people and businesses move money around the world. Your work will contribute to products and services that help millions of customers stay connected globally. Own Meaningful Outcomes: We empower our people to take ownership, make decisions, and drive real impact. You'll have the opportunity to shape solutions, challenge the status quo, and see the results of your work firsthand. Grow with Us: As a fast-growing global fintech, we offer opportunities to learn, develop new skills, take on new challenges, and advance your career across functions and geographies. Collaborate with Exceptional People: Work alongside talented colleagues from diverse backgrounds and disciplines who are united by a shared ambition to build, innovate, and deliver great outcomes for our customers. Move Fast and Make Things Happen: We value action, curiosity, and continuous improvement. You'll be part of a culture that encourages experimentation, embraces change, and focuses on delivering meaningful results. Be Part of Our Journey: We're building the future of the global money movement. Join us at an exciting stage of growth where your ideas, expertise, and contributions can help shape what's next.

Location: Amsterdam, Netherlands; Berlin, Germany; United Kingdom About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role We are looking for a Senior Software Engineer to build the event-processing pipelines and services that turn Nebius product usage into revenue. You will work on systems that process a continuous stream of usage events, where correctness and failure recovery matter as much as throughput. The output is money: a silently dropped or double-counted event is a real financial error. Usage of every Nebius product arrives as a stream of events. Our pipelines and services ingest, validate, enrich and price it in near real time, and deliver the results to invoicing, reporting and customer-facing account management. In this role, you will: Build stateful streaming pipelines that compute billed consumption in near real time. Develop and operate Go services that ingest usage events, move data between our storage systems and deliver consumption data to users through usage APIs and billing data exports. Guarantee correctness under failures: idempotency, exactly-once processing and reconciliation. Operate transactional storage, persistent queues and change data capture under high throughput. Build reusable streaming infrastructure rather than solving each use case independently. Improve the reliability, scalability, latency and observability of the billing platform. Take end-to-end ownership of your systems: design, implementation, reliability and deployment. We expect you to have: Strong software engineering fundamentals. Professional experience building and operating backend, streaming or data-intensive systems. The ability to reason about consistency and data correctness under failures. Experience with databases, messaging systems or event-processing platforms. The ability to investigate unfamiliar systems and solve problems without an obvious predefined solution. The ability and willingness to learn the team's technology stack. It will be an added bonus if you have: Experience with a stateful stream-processing framework such as Apache Flink or Kafka Streams. Experience designing streaming pipelines. Go development experience. Experience operating services in Kubernetes. Technology stack Go, Python Apache Flink YDB YTsaurus Messaging and event-streaming systems Kubernetes #LI-ET2 Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.