Instrumentation Automation Service Engineer I in San Francisco

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: Experience building systems in adversarial, fast-evolving environments Are comfortable with ambiguity and novelty Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. Significant experience

About the Team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. About the Role OpenAI is seeking a System Power Engineer to characterize, measure, and optimize power consumption across our embedded hardware products. In this role, you will work closely with Electrical Engineering and system software teams to build power test automation, measure subsystem-level power usage, and drive improvements that directly impact battery life, thermal behavior, charging performance, and system reliability. You will help establish the methodologies and metrics used to understand and improve power efficiency across real-world product experiences, from controlled lab environments to representative day-in-the-life usage scenarios. This role requires hands-on experience with embedded hardware platforms, power instrumentation, and the analysis of power profiles and system behavior. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. In this role, you will: Define and develop power testing automation to evaluate system behavior across a range of workloads and operating conditions. Measure subsystem-level power consumption using power breakout probes and other lab instrumentation. Develop and execute power characterization tests spanning basic workloads, complex mixed-use scenarios, and representative day-of-use experiences. Partner closely with Electrical Engineers to identify opportunities to improve system power efficiency. Collaborate with software engineering

What you’ll do Execute weekly system-level exploratory testing across the scanner and supporting software; log and triage issues with clear reproduction steps. Work with engineering to debug root cause and validate fixes. Help maintain the DHF and traceability between user needs, design requirements, tests, and results. Own practical test execution logistics (fixtures, test data, environments, calibration artifacts) and keep things repeatable. Help build the continuous testing strategy: automated tests where feasible, plus structured manual and system tests. Support V&V activities, including coordination with external partners as needed. What we’re looking for Strong hands-on testing instincts for complex electromechanical systems with substantial software. Ability to write clear bug reports and communicate risk/impact. Experience building and maintaining test plans/protocols; comfort operating lab equipment and debugging across layers. Useful experience Experience testing complex systems end-to-end (automation where it pays off, plus hands-on hardware/instrumentation). Medical device or other safety-critical environments and comfort translating risk into practical test coverage.

About the Team Customer education helps customers and partners build the practical skills and confidence to use AI and OpenAI products safely and effectively. The team focuses on role- and skill-based learning paths, practical content, and product experiences that accelerate learning in the workplace. It brings together learning and enablement expertise, field insight, product signals, and measurement to improve learner and business outcomes. Together, these experiences will help enterprise users build practical AI skills, apply them with confidence in their work, and demonstrate what they can do. Employers will gain a clearer view of workforce skills and progress, helping them recognize capability, focus development where it matters most, and build confidence in workforce readiness. About the Role We’re looking for a full-stack engineer to define and build a new class of learning experiences. This is an early-stage product area where technical judgment, product sense, and learner empathy are critical. You will be setting a technical vision for how people use AI to learn how to use AI, safely and beneficially. This is a hands-on, 0-1 product engineering role with broad technical and product ownership. You’ll set direction, make foundational decisions, and ship the first versions of experiences that can grow into the default way people learn at work. You will drive full-stack product experiences end to end, from prototype through launch, instrumentation, iteration, and production hardening. The work spans interaction design, frontend implementation, backend APIs and services, learner state, content and runtime integration, telemetry, evaluation, reliability, safety, accessibility, and launch readiness. You’ll work closely with our education, GTM, and engineering teams to translate how people learn into products people want to use. bring role- and skill-based learning paths into the product, designing coaching, feedback, and adaptive support which responds to each lea

Work Flexibility: Field-based Overview As a Clinical Specialist at Stryker, you will help improve orthopedic surgeries around the world and play a direct role in our mission of making healthcare better. In this role, you will build deep clinical and technical expertise across both robotic (Mako SmartRobotics™) and manual orthopedic procedures. You will support surgeons in the operating room by assisting with pre-operative planning, case preparation, system setup, and real-time procedural workflows to ensure safe, accurate, and efficient outcomes. You will gain hands-on experience working with Mako technology—including CT-based planning, implant sizing, registration, and intra-operative support—while also developing strong competency in manual procedures, instrumentation, and OR protocols. Through shadowing experienced team members, supporting product demonstrations, and participating in labs and education programs, you will learn the systems, processes, and best practices that define world-class clinical support. This role requires adaptability, steady composure, and strong problem-solving in a fast-paced surgical environment. Because patients’ needs don’t follow business hours, you will also participate in on-call coverage, including evenings, weekends, and holidays, to ensure uninterrupted support for urgent cases and time-sensitive customer needs. What You Will Do Gain competency in solo case coverage for manual and robotic procedures through hands-on training. Assist surgeons with pre-operative CT-based planning, implant sizing, and positioning using advanced software. Support full case preparation, including instrumentation checks, equipment setup, and OR readiness. Troubleshoot technical issues confidently and efficiently in the operating room. Learn and support workflow for daily account

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking an Electrical Engineer to build and own the electrical backbone of our robotic actuator dynamometer and test infrastructure. You will design, integrate, and operate the load motor drives, power distribution, instrumentation wiring, DAQ interfaces, and safety systems that make high-performance robotic actuator testing repeatable, safe, and scalable. This role spans hands-on lab execution and system architecture: selecting and commissioning power electronics, designing robust test-cell electrical systems, bringing up sensors and DAQ, and partnering with mechanical and software engineers to turn robotic actuator hardware into trustworthy data. In this role, you will Own the electrical architecture of dynamometer and actuator test cells, from mains distribution and protection through load motor drives, braking, and auxiliary power. Specify, integrate, commission, and tune motor drives and load machines for robotic actuator torque, speed, efficiency, thermal, and durability testing. Design power distribution, grounding, shielding, cable routing, and connectorization for high-current, high-voltage, and low-level measurement systems. Integrate torque, position, speed, temperature, voltage, current, vibration, and other instrumentation from robotic actuators into DAQ and control systems. Develop electrical schematics, wiring diagrams, panel layouts, harness documentation, and test-cell interface definitions. Build, debug, and maintain test-cell electrical hardware, rapidly diagnosing noise, EMI, grounding, drive, sensor, and power-q

About the Team OpenAI Consumer Devices is building the next generation of products that bring powerful AI into people’s everyday lives. Guided by OpenAI’s mission to ensure AGI benefits all of humanity, our team combines world-class researchers, engineers, designers, and operators who care deeply about creating useful, intuitive, and responsible technology. You’ll have the opportunity to work alongside exceptional people on ambitious, zero-to-one challenges at the intersection of hardware, software, and AI. This is a chance to help define an entirely new category of products—and shape how people experience AI in the future. Our team works across custom silicon, embedded systems, operating systems, and cloud services to build reliable consumer devices and the platforms behind them. We connect kernel development with the broader software stack to deliver complete product capabilities. About the Role As an Operating Systems Engineer focused on the Linux kernel, you will design, develop, and maintain the kernel capabilities that underpin OpenAI’s consumer devices. You’ll bring deep expertise in one or more Linux kernel subsystems and carry solutions through the higher-level software stack. Your ownership will extend into the userspace services, libraries, tools, and interfaces needed to deliver complete product features. You’ll shape the boundaries between kernel and userspace, make design decisions across the stack, and see your work through development, integration, and production. In this role, you will: Build kernel capabilities: Design, implement, and maintain Linux kernel subsystem changes that support device capabilities and product requirements. Own features across the stack: Choose appropriate kernel and userspace boundaries, and build the interfaces and supporting components needed to deliver reliable features in shipped products. Debug complex system behavior: Use tracing, profiling, instrumentation, and diagnostic tools to resolve correctness, concurrency, p

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Job Title: Software Engineer II, Data Analytics and Engineering Intro: We’re looking for a Software Engineer II, Data Analytics and Engineering to improve the quality, reliability and velocity of data science and product development at Pinterest. You’ll build scalable data foundations, analytics tooling and analysis pipelines that enable trusted, self-service access to datasets, insights and metric investigations across cross-functional teams. What you’ll do: Develop and document practical instrumentation and experimentation standards, then partner with product engineering teams to apply them to priority product development work. Build and improve scalable analysis pipelines and tooling that produce reliable insights at scale and strengthen understanding of key data structures and metrics. Create tools and processes that enable Data Scientists a

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry is looking for an Engineering Manager to lead our Growth team (internally called "Value Discovery") and help expand our product-led business by helping customers discover and get the most out of our platform. At Sentry, we do growth with an explicit bias for customer value. Our experiments are rooted in strong product sense and empathy for developers, not conversion pressure. We never surprise developers with new charges or push features they don't need. In a binary tradeoff between doing good by the customer or good by the business, the customer always wins. You'll collaborate closely with several areas of the business including Product, BizOps, Data, Design, and GTM to identify the moments in a developer's workflow where Sentry can deliver more value, make that value easier to find, and support that your approach works with data. In this role you will You'll lead a team of engineers, set its priorities, and be accountable for the metrics it moves. This is a new role, and the roadmap is yours to define and execute in partnership with design and data teams. Lead work across Sentry's self-serve funnel — signup and onboarding, first-run activation moments in-product, trial and upgrade paths, and pricing and billing surfaces in partnership with the Billing team — largely in our Python/Django and TypeScript/React codebase Evolve our experimentation foundations, in close partnership with our Data team — flagging, instrumentation, and readouts are real but far from finished Run a fast, disciplined experimentation loop where hypotheses are argued before they're built Hold conversion and activation alongside ch

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. As an early member of the Observability Team, you will be pivotal in building and shaping the observability experience for our internal and external customers. By joining this team, you’ll have a direct impact on the reliability and operational excellence of Basetens product systems. As Baseten scales its infrastructure across different cloud providers and diverse hardware, the volume and complexity of operational data is growing by orders of magnitude. This team is responsible for building high-throughput ingest pipelines, cost-efficient storage, and agentic diagnostic tools to ensure that we can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become more complex. RESPONSIBILITIES Design and build scalable telemetry ingest and storage pipelines for metrics, logs, and traces across Baseten’s multi-cloud infrastructure Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliabi

What you’ll do Be the generalist EE for the scanner system: integration, bring-up, debugging, and making the electrical side of the device reliable and serviceable. Own ultrasound experimentations that feeds the image reconstruction team Design and execute experiment setups for transducer characterization (element sensitivity, bandwidth, cross-talk mapping, beam profile measurements) and ex vivo / phantom clinical testing. Acquire, process, and analyze RF and baseband signals for data quality assessment and benchmarking. Design simple boards and adapters as needed (monitoring, power/safety, interface/conditioning), and take them from prototype through a stable revision. Prototype quickly, then harden what works: wiring/harnessing, grounding, safety interlocks, and reliable integration across subsystems. Own practical test setups and documentation (fixtures, scripts, procedures) that make experiments repeatable and results comparable over time. What we’re looking for Strong hands-on EE background with experience building, debugging, and iterating on real systems in the lab. Solid understanding of signal processing fundamentals — knows what to measure, how to condition and digitize it, and how to evaluate signal quality in the context of an imaging system (SNR, bandwidth, dynamic range, artifacts). Comfortable spanning system integration + occasional design work (schematics/layout reviews or light PCB design) in a fast-moving environment. Ability to work at the boundary between hardware and algorithms: measure reality, communicate constraints, and help close gaps vs simulation. High agency and practicality: able to set up experiments, get trustworthy data, and unblock others on a lean team. Useful experience Analog/mixed-signal, or high-speed data capture experience; strong instincts for instrumentation and noise/debugging. Ultrasound or acoustic sensor handling: hydrophone calibration and field mapping, transducer impedance characterization, element-level sensitivity

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

Datadog's Forward Deployed Engineering function is in an active growth phase, and the FDE Lead will play a central role in shaping what comes next. Working in close partnership with the Head of Datadog for Startups and Forward Deployed Engineers, and the existing FDE team, you will help define and expand the FDE framework, build out the structures and processes that allow the team to operate at scale, and extend the program's reach well beyond any single customer segment. This role sits at the rare intersection of sales, execution, program design, and hands-on engineering leadership. You are part field technical leader, part program architect, and part cross-functional connector. You will help determine what the FDE motion looks like at Datadog, contribute to its playbook, and push the boundaries of what the team can deliver. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Evolve and scale the FDE operating model end to end: engagement intake, scoping, sprint delivery, handoff back to account teams, and the success metrics (time-to-value, adoption lift, ARR influence, NPS) and reporting infrastructure that support them. Build out a catalog of FDE offerings spanning observability quickstarts, custom integration development, LLM/AI observability accelerators, CI/CD pipeline instrumentation, and cost optimization deep dives, and contribute to their pricing and business models, including free-to-paid conversion plays, paid deployment packages, and post-deployment success motions. Capture product and feature gaps uncovered during deployments, translate them into structured prioritized briefs, and partner with PM and Engineering to strengthen the field-feedback channel that informs roadmap decisions on a regular cadence. Hire, onboard, an

About the Team We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role OpenAI is looking for an experienced Performance Engineer to help us scale the performance, reliability, and efficiency of our systems. In this role, you'll apply deep technical expertise to optimize infrastructure and application-level performance across mission-critical products like ChatGPT and our developer API. You’ll work cross-functionally with teams building core services, training models, and developing real-time user experiences to push our latency, throughput, and cost-efficiency to the next level. We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack. In this role, you will: Analyze and optimize performance across application, middleware, runtime, and infrastructure layers—networking, storage, Python runtime, GPU utilization, and beyond. Develop tooling and metrics that provide deep observability into system performance. Collaborate closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements. Influence architecture and design decisions to prioritize latency, throughput, and efficiency at scale. Lead investigations into high-impact performance regressions or scalability issues in production. Drive performance testing strategies and help define SLAs/SLOs around latency and throughput for critical systems. You might thrive in this role if you: Have 7+ years of experience in software engineering with a strong tr

Job Description: Data Scientist, B2B Demand Generation, Growth & Measurement About the Role We are hiring a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will help us understand which marketing investments create incremental demand, qualified pipeline, and revenue and how to scale them efficiently. Our mandate is to build a rigorous, full-funnel view of how B2B marketing creates demand and moves prospects from awareness and engagement to qualified opportunities, closed-won revenue, and expansion. You will shape how we measure marketing impact and influence across channels, campaigns, audiences, and account segments. In this role, you will partner closely with B2B Marketing, Demand Generation, Growth, Sales, RevOps, Finance to connect marketing activity to qualified pipeline, customer acquisition, and efficient revenue growth. What You’ll Do Define north-star, leading, and guardrail metrics for B2B demand generation, including account engagement, qualified leads and opportunities, sourced and influenced pipeline, conversion rates, pipeline velocity, and incremental ARR. Design and execute measurement and experimentation strategies across channels and campaigns, using randomized tests, audience or geographic holdouts, lift studies, quasi-experimental methods, and other causal approaches suited to long B2B sales cycles. Analyze channel, audience, campaign, creative, content, landing-page, and account-segment performance to identify the drivers of qualified demand, funnel conversion, pipeline quality, and incremental revenue. Partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve instrumentation, campaign taxonomy, CRM data quality, lead-to-account matching, and the operating cadence for acting on measurement insights. Build AI-native measurement and decision-support workflows, using LLMs and agents to synthesize campaign performance, surface growth opportunities, and h