Instrumentation Automation Service Engineer I in United States

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

Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Mechanical Engineer is responsible for end-to-end hardware ownership of components and sub-systems for the KARNO generator, taking designs from CAD through prototype, test, and validation. Working across mechanical, electrical, software, and performance teams, this role designs and troubleshoots complex thermal and mechanical systems that must perform reliably across extreme operating environments and a wide range of fuels. The position exists to advance the development of Hyliion's fuel-agnostic power generation technology through hands-on, test-driven engineering and disciplined design execution. Duties and Responsibilities Own hardware components and sub-systems end-to-end—from concept through durability, manufacturability, serviceability, cost, weight, and validation—taking designs from CAD to hardware running on a test stand. Design components and sub-systems that must survive extreme thermal environments, perform across a wide range of fuels (20+), and push the boundaries of metal additive manufacturing. Create 3D models in NX and generate 2D prints with full GD&T per ASME Y14.5. Perform design checking and print review to ensure tolerances, processes, and material specifications align with Hyliion's GD&T standards (ASME Y14.5). Conduct fluid and thermal systems design and optimization. Perform structural and thermal FEA (ANSYS or equivalent). Install, calibrate, and read instrumentation for pressure, temperature, flow, strain, and acceleration in lab environments. Execute prototype build, test, and validation cycles early and often to identify and resolve issues in the lab rather than the field. Collaborate cross-functionally

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

ROLE SUMMARY We are seeking a highly motivated individual to join our high content imaging lab within the Discovery Biology and Pharmacology (DBP) group at the vibrant Groton campus in Connecticut. DBP is responsible for hit-identification, lead optimization, and molecular characterization of our small molecules and has teams focused on high-throughput screening, DNA-encoded libraries, pharmacology, protein homeostasis platforms, cellular models, functional genomics, and high-content imaging. The group is highly integrated with other groups in Medicine Design including Chemists, Structural Biologists, and Computational Scientists, and supports the small molecule portfolio across multiple therapeutic areas. The individual in this role will bring in rich experience in high content imaging and high throughput flow cytometry, and apply them to support our diverse small molecule portfolio spanning various therapeutic areas. ROLE RESPONSIBILITIES High-content imaging assay design, development, and optimization: Apply a broad range of imaging and flow cytometry assay technologies to address project needs. Independently develop, optimize, and troubleshoot high-content imaging and flow cytometry assays. Imaging data analysis and interpretation: Design and implement advanced image-analysis workflows, build complex analysis algorithms, and streamline data processing to support medium- to high-throughput screening. Translate imaging data into clear, actionable biological insights. Imaging infrastructure management and continuous improvement: Partner with team experts to support high-content imaging and flow cytometry instrumentation, implement software solutions that enable advanced imaging applications and data analysis, and continuously improve ima

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 115,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Position Overview The Senior Clinical Laboratory Scientist will be responsible for performing moderate and high complexity laboratory testing on patient specimens, interpreting and reporting patient results, performing quality control and quality assurance procedures, assisting Laboratory Leadership with advanced laboratory duties, and complying with all applicable local, state, and federal laboratory requirements. The Senior Clinical Laboratory Scientist will continually display excellent initiative in all aspects of their work, contribute to projects and discussions in addition to daily laboratory testing and consistently performing to high standards. Leadership is demonstrated in technical troubleshooting of laboratory instrumentation and processes as well as laboratory quality improvements, health and safety, and training of laboratory staff. Essential Duties include but are not limited to : Perform moderate and highly complex laboratory tests, procedures, and analyses according to the laboratory’s standard operating procedures with minimal supervision. Perform, review, and document laboratory quality control procedures. Identify potential problems, determine potential solutions, and take appropriate action in order to maintain a high level of quality in test processes and results. Achieve and maintain competency on laboratory tasks. Participate in research, validation, and/or implementation of new procedures and/or technologies. Mainta

About the team The Monetization Data Platform team builds the trusted data and platform foundations that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences. We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business. About the role We are looking for a Data Engineer to improve and build the next generation of our monetization data platform. You will own high-impact systems end to end, from product instrumentation, source ingestion, and canonical modeling through quality controls, observability, and delivery to downstream consumers. This is a hands-on role for an engineer who enjoys solving ambiguous product and data problems, designing durable architectures, and partnering closely with Product Engineering, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into trusted, scalable data products and platform capabilities. In this role, you will Design, build, and operate large streaming and batch data pipelines that process product, financial, and operational data from a variety of internal and external systems. Develop canonical data models and reusable data products for domains such as product usage, pricing, billing, ads, payments, revenue, and the general ledger. Establish strong guarantees for data accuracy, completeness, freshness, lineage, reconciliation, and auditability. Build frameworks and platform capabilities that improve developer productivity and make it easier for teams to launch, measure, and iterate on m

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will:

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.

What you'll do Run human-subjects recording sessions end-to-end: participant prep and fitting, sensor configuration and calibration, stimulus delivery, real-time signal monitoring, and session documentation. Own daily system QC for a one-of-a-kind sensing instrument: baseline noise recordings, per-sensor health checks, log review, and escalation of anomalies before they touch a dataset. Own participant operations: recruitment coordination, scheduling, screening, consent, and compliant handling of participant records. Stand up and maintain the operational backbone of the program: SOPs for acquisition, QC, and participant workflows — documentation that survives you. Handle first-pass data operations: file conversion, organization, metadata, and quality review in Python. Partner daily with the program lead to refine acquisition protocols and improve system performance over time. What we're looking for Hands-on experience acquiring physiological or imaging data from human participants in a clinical or research setting Obsessive consistency and attention to detail: you notice when something is off and you don't let it slide. Professional, patient, and calm with research participants — sessions succeed or fail on how people feel in the room. Basic scripting ability (Python and/or shell) for QC and data-handling tasks, or clear aptitude and motivation to build it. High ownership of the unglamorous parts: scheduling, documentation, tidy data hygiene. Discretion — parts of this program are not yet public. We'll walk you through the specifics, including the exact technology you'd be operating, in the first conversation. Useful experience Controlled or low-noise recording environments and highly sensitive instrumentation. Physiological signal-processing tools in Python. Human-subjects research administration (IRB protocols, consent workflows). Research studies involving structured tasks or sensory protocols with human participants.

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Data Engineering team at Roblox plays a crucial role in enabling the company's success by developing and maintaining highly leveraged Core Data Sets, frameworks, and tooling to support the growing demand for analytics. As a Principal Data Engineer, you will work to define the data ontology for all of Roblox, establish best practices and standards for data operations and lifecycle management, design and build analytics tooling and frameworks, and influence event instrumentation. Additionally, this role is highly cross-functional, requiring close collaboration with Data Science, Experimentation, and Machine Learning teams to understand customer requirements and analytics applications, as well as with Data Infrastructure and Storage teams to develop integrated solutions. Join us and be a part of a dynamic team driving innovation and growth at Roblox. You Will: Partner with Data Science, Data Platform, Product, and Engineering to collect requirements to define the data ontology for all of Roblox Lead and mentor a growing team of Data Engineers to support Roblox's ever-evolving data needs Design, build, and maintain efficient and reliable batch and streaming data pipelines to mod

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. The Data Engineering team at Roblox plays a fundamental role in enabling the company's success by developing and maintaining highly leveraged Core Data Sets, frameworks, and tooling to support the growing demand for analytics. As a Senior Data Engineer, you will work to define the data ontology for all of Roblox, establish standard methodologies for data operations and lifecycle management, design and build analytics tooling and frameworks, and influence event instrumentation. Additionally, this role is highly multi-functional, requiring close collaboration with Data Science, Experimentation, and Machine Learning teams to understand customer requirements and analytics applications, as well as with Data Infrastructure and Storage teams to develop integrated solutions. Join us and be a part of a dynamic team driving innovation and growth at Roblox. This role will report to our Engineering Manager on the Data Engineering team. You Will: Partner with Data Science, Product, and Engineering to collect requirements to define the data ontology for all of Roblox Lead and mentor a growing team of Data Engineers to support Roblox's ever-evolving data needs Design, build, and maintain efficient an

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a senior software engineer on the Cell Platform team at Roblox, you will build systems that Roblox engineers use to create and deploy resources onto Kubernetes. Our engineers deploy their services in a complex, hybrid, multiple-cluster, K8s environment. The Cell Platform manages this complexity for our users, with tools, APIs, K8s controllers, and UX, simplifying infrastructure for our internal customers. You Have: A desire to work on critical, large-scale distributed systems An appreciation of observability and instrumentation and tooling to make your life easier 3+ years of experience as software engineer Bachelor's degree in Computer Science or an equivalent field You will: Build our Roblox-wide control plane using Kubernetes primitives (and plenty of custom resources) Work on the interface of the few hundred person infrastructure organization to the thousands of Roblox engineers Write and review high quality code and tests (largely Golang) Work on a team that cares about inclusivity and shipping For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related

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