Python Engineer in United States

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: We’re seeking an experienced UX Researcher to define and scale how we evaluate Notion’s AI-powered experiences—focusing on what “good” looks like not only for model output quality, but for the end-to-end product experience where people discover, set goals, delegate work, review results, and build trust over time with AI. This role sits at the intersection of research craft and evaluation operations: you’ll run studies that uncover user mental models, expectations, and failure/recovery behaviors, then translate those insights into reusable rubrics, workflows, and measurement approaches that product, design, engineering, and data science can apply consistently. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Define what “good” looks like (frameworks & rubrics): Establish clear, reusable evaluation criteria that reflect real user expectations—helpfulness,

Job Requisition ID # 26WD100617 Position Overview Autodesk is shaping the future of the design and make industries by helping our customers navigate a rapidly evolving AI-driven landscape. Supporting our Autodesk AI initiatives, you will help us understand how AI and new business models are reshaping the competitive landscape across Manufacturing, AECO (Architecture, Engineering, Construction, and Operations), and Media and Entertainment. This is an individual contributor role on a team with deep business, industry, and technical experience. A successful candidate builds with AI by default, not as a tool added on top. The way competitive intelligence gets done is changing faster than most business functions can adapt. We’re hiring for that gap. You will spend as much time building the systems that produce our intelligence as you will producing it. Location : We support hybrid work, and you work near our Portland, Oregon, or San Francisco, California offices. Responsibilities Build and maintain the automated systems that produce our intelligence, including source monitoring and refresh cadences Find the parts of our process that shouldn’t be manual anymore and fix them without waiting for permission Track how AI is changing our markets, following competitors, startups, funding, product releases, partnerships, research, talent movement, and regulatory shifts Work directly with business functions, product management, engineering, and technical benchmarking to define target markets, map competitive landscapes, size opportunities, identify gaps, and test market and com

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary We are seeking a skilled and analytical Senior Product Analytics Associate to lead the development and execution of a data-driven product roadmap. The ideal candidate will have a deep understanding of product analytics, strong problem-solving skills, and experience working with cross-functional teams to support strategic initiatives. As a Senior Product Analytics Associate, you will work closely with cross-functional teams including engineering, product, and clinical operations. Roles and Responsibilities: Define, track, and report on product metrics including performance and profitability Build and maintain robust data transformation models using dbt (or similar frameworks like Dataform or SQL-based ETL tools) to ensure analytics-ready datasets Design and interpret A/B tests; when A/B testing is not feasible, apply causal inference methods (e.g., Diff-in-Diff, Propensity Score Matching) to determine product efficacy. Develop ROI projections for analytics projects to prioritize deliverables by business impact Tell compelling stories through data, articulating technical information to a non-technical audience Build and maintain Power BI dashboards to

Lead Analyst Company: The Boeing Company Boeing F-22 Mission Systems team is hiring for a Lead Analyst located in Berkeley, MO . As Lead Analyst, you will be responsible for analyzing engineering solutions for the F-22 Raptor, including both enhancing existing field units with the addition of new capabilities as well as architecting and testing completely new systems. In this role you will be joining a cross-functional team to progress our products through the development lifecycle. Position Responsibilities: Leads analysis and translation of complex requirements into system architecture, hardware and software designs and interface specifications. Must be able to work in a fast-paced, collaborative environment, engaging with multiple teams and being responsive to agile requirements and critical path customer need dates. Collaborates with Responsible Engineers, customer technical staff, suppliers, and Lockheed Martin teammates to develop and document complex electronic and electrical system requirements for F-22 avionics sub-systems and weapon system architecture Analyzes and translates requirements into system architecture, hardware and software designs and interface specifications in support of lab and operational environments Reviews test data, including off-nominal data, for accuracy, quality and/or fidelity prior to delivery to customer This position is expected to be 100% onsite. The selected candidate will be required to work onsite at one of the listed location options. This position requires the ability to obtain a US Secret Security Clearance for which the US Government requires US Citizenship A final Secret Clearance

We are seeking an experienced Senior Generative AI Developer to help drive the design, development, and integration of state-of-the-art Generative AI and agentic AI solutions across our enterprise Controls Technology platform. You will collaborate with cross-functional teams, contribute deep technical expertise in context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration, and play a key role in delivering scalable, grounded AI solutions to enhance automation and operational efficiency. This role centers on architecting robust applications and agent systems on top of pre-trained and hosted foundation models — not on training or fine-tuning models. Key Responsibilities Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges. Architect advanced context engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production. Design and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG) . Build and optimize RAG systems , including hybrid search, multi-vector retrieval, and re-ranking pipelines. Design and implement knowledge graphs and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains. Architect agentic workflows and multi-agent systems using Google Agent Development Kit (ADK) and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer. Design robust agent harnesses — governance, constraints, feedback loops, state/session management, and

Graphcore Director-Post Silicon Validation (Functional) Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Austin, Texas which will play a central role in Graphcore's work building the future of AI computing. We are developing the next generation of AI compute, a large-scale system-on-chip (SoC) designed to power future high-performance AI systems. Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team validating cutting-edge, high-performance AI chips and platforms. You will play a key role in supporting new product introductions and validation. You will lead a team delivering post-silicon validation across the full AI SoC, working across silicon, firmware, and platform levels. The role requires a deep technical understanding, strong hands-on debug experience, and the ability to collaborate effectively with hardware, software, and systems engineering teams. Working within the Validation team, you will be involved with bringing first silicon to life, functionally validating it and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to provide technical guidance to other engineering team members. In this role, you can leverage our experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. Th

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and

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 ship AI products. THE ROLE As a Global Capacity Manager focused on TPUs at Baseten, you will lead the "engine room" for our non-NVIDIA accelerator fleet, architecting, securing, and optimizing the Google Cloud TPU (and broader emerging accelerator) capacity that powers our customers' AI workloads. You'll own the end-to-end journey of capacity management for this fleet, from securing large-scale TPU pod allocations to building the automation that ensures reliable uptime across multi-cloud environments. This role is a great fit for entrepreneurial engineers who want to bridge the gap between high-finance asset management and deep infrastructure engineering, with a specific focus on the TPU ecosystem. You will act as the fleet orchestrator for Google's TPU architecture, ensuring Baseten never experiences a capacity outage while maintaining elite unit economics as we diversify beyond NVIDIA. To be clear, this is a high-stakes engineering role. You will be hands-on with Kubernetes orchestration while also leading specialized pods focused on the latest generation of TPU hardware, like Google's Trillium (v6e) architecture, and partnering closely with the Model Performance (MP) team to ensure workloads are tuned for TPU-specific execution. EXAMPLE INITIATIVES The TPU Frontier: Architecting the infrastructure readiness and deployment strategy for Baseten's TPU clusters, including pod slicing and topology planning Global Workload Orchestration: Bui

About the Team OpenAI's Industrial Compute organization builds and operates the infrastructure required to train and serve frontier AI models. The Capacity Planning team connects rapidly changing research and product demand with the compute, networking, storage, power, data center, hardware, and operational resources required to make that demand executable. About the Role We are seeking a Technical Program Manager to build and lead capacity planning across OpenAI's large-scale AI infrastructure. You will translate uncertain workload demand into clear infrastructure requirements, allocation decisions, supply commitments, activation priorities, and long-range capacity strategies. This role sits at the intersection of research, engineering, infrastructure, finance, sourcing, deployment, and operations. You will create the planning models, operating cadences, governance mechanisms, and source-of-truth systems that allow teams to understand what capacity is required, what is available, what is at risk, and what decisions must be made. This is not a finance-only forecasting or reporting role. Success requires technical fluency across the infrastructure stack, strong analytical judgment, and the ability to move consequential decisions forward when requirements, timelines, and supply conditions change quickly. Key Responsibilities Own capacity-planning processes across near-term workload allocation, quarterly execution, and longer-range infrastructure horizons. Translate research, training, inference, and product demand into compute, accelerator, cluster, networking, storage, rack, power, and site requirements. Develop scenarios that make assumptions, confidence levels, constraints, sensitivities, and decision points explicit. Reconcile requested demand against contracted, delivered, installed, activated, and workload-usable capacity. Partner with research and engineering teams to understand workload priorities, technical dependencies, utilization patterns, and changing req

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 ship AI products. THE ROLE As a Global Capacity Lead at Baseten, you will lead the "engine room" of the company, architecting, securing, and optimizing the global GPU fleet that powers our customers' AI workloads. You’ll own the end-to-end journey of capacity management, from securing multi-million dollar GPU clusters to building the automation that ensures 99.9% uptime across multi-cloud environments. This role is a great fit for entrepreneurial engineers who want to bridge the gap between high-finance asset management and deep infrastructure engineering. You will act as the fleet orchestrator for the world's most advanced chips, ensuring Baseten never experiences a capacity outage while maintaining elite unit economics. To be clear, this is a high-stakes engineering role. You will be hands-on with Kubernetes orchestration while also leading specialized pods focused on the next generation of hardware, like NVIDIA’s Blackwell (B200) architecture. EXAMPLE INITIATIVES The B200 Frontier: Architecting the infrastructure readiness and deployment strategy for Baseten's first Blackwell GPU clusters. Global Workload Orchestration: Building "Multi-cloud Capacity Management" systems to move customer workloads seamlessly across regions to optimize cost and latency. Precision GPU Triage: Developing automated Go-based operators to identify, cordon, and repair unhealthy H100 nodes in under an hour. The Supply Chain of Intelligence: Partnering with lead

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 ship AI products. THE ROLE We're hiring a Product Data Scientist to establish how product decisions at Baseten are made with data. You'll work directly with Product and Engineering, alongside GTM to determine measurement, strategy, experimentation and implementation. This is a foundational, hands-on role. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape product strategy. You'll work from clickstream and product events through inference telemetry and observability data, helping Baseten make faster decisions about reliability, performance, adoption and developer experience. RESPONSIBILITIES Partner directly with Product and Engineering: frame the questions that matter, define success criteria, and turn analysis into roadmap, launch, and prioritization decisions. Define how product success is measured: establish metrics across activation, adoption, retention, expansion, reliability and user experience. Support experimentation and launches: design measurement plans, analyze A/B experiments and controlled rollouts, and translate results into product decisions. Diagnose reliability and scaling behavior: join customer signals with request, replica, deployment, and cluster telemetry to find patterns in release bottlenecks, unhealthy replicas, and models without traffic. Define the enterprise customer journey and measure feature adoption

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. About the Role Ema sells through two motions that behave very differently, and today they share one pipeline, one CRM, and one forecast. Direct enterprise — field Account Executives landing Fortune 2000 logos at $250K+ initial contract value and expanding past $500K, into buying committees that include IT, security, data governance, and procurement. Partner-led — global systems integrators and ISVs, including Teleperformance, PwC, Wipro, NTT Data, Hitachi, KPMG, Atos, ADP, Microsoft, and Google, who deploy Ema's Frontier Apps to their own clients. In some cases the partner embeds Ema inside their own product and owns the end-client relationship entirely. Those two motions require different definitions, different attribution rules, and different quota treatment. Building that distinction — and the systems, reporting, and compensation logic that sit on top of it — is the core of this role. This is the first dedicated Revenue Operations hire supporting the US go-to-market organization. You will be building the function, not maintaining one. What You Will Own Forecasting and pipeline management Own the weekly forecast process and cadence across direct and partner motions, and report fo

About the Team OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Marketing team helps deeply understand customer audiences and market dynamics, influence the development of the right products, build sustainable and customer-aligned monetization models, and drive awareness, adoption, and usage across OpenAI’s products and platform. We take a data-driven approach to understand markets, develop monetization strategies, and uncover customer needs that shape product strategy and messaging. We partner closely with Sales, Partnerships, Product, Engineering, Research, Comms, and Design to deliver a cohesive end-to-end customer experience and lead go-to-market efforts for new product launches across channels. About the Role We’re looking for a Marketing Scientist to join OpenAI’s Ads Marketing Science function. Reporting to Marketing Science leadership, you’ll be a senior individual contributor who combines rigorous measurement expertise with strong client judgment and hands-on execution. Your mission is to help OpenAI Ads prove and improve advertisers’ media performance. You’ll work with sales, partners, and clients supporting all forms of measurement including verification, attribution, incrementality, brand, marketing mix modeling (MMM), and scalable advertiser reporting, connecting sound methodology to decisions advertisers can act on. You will partner closely with Sales on key advertising accounts and with Product, Engineering, Data Science, Partnerships, Legal, and Privacy. Initial priorities include advancing incrementality measurement, helping onboard measurement partners to privacy-forward measurement workflows and integrations, and creating reusable programs, tools, agents, skills, and workflows that let sales and clients access high-quality Marketing Science support at scale. This role is based in either San Francisco or New York, and follows a hybrid schedule (Monday-Wednesday). In th

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Micron’s Chemistry Lab plays a critical role in advancing semiconductor technology by developing analytical methods that support materials understanding, process development, defect characterization, and next-generation memory innovation. The team applies advanced chemical, optical, and surface characterization techniques to solve complex materials challenges across semiconductor manufacturing and research. We are seeking a highly motivated summer intern to contribute to advanced spectroscopy and nanoscale characterization projects focused on semiconductor thin films, surfaces, interfaces, and process-induced material changes. Working alongside scientists and engineers in Corporate Labs, the intern will develop and apply spectroscopy-based characterization methods, analyze complex materials datasets, and gain experience in experimental design, data analytics, and semiconductor materials research within an industrial laboratory environment. Responsibilities Conduct experiments using advanced spectroscopy and microscopy techniques to characterize semiconductor thin films, surfaces, interfaces, and related materials. Collect, process, analyze, and interpret spectroscopy data, including photoluminescence, fluorescence lifetime, Raman, and AFM-IR datasets, and develop visualization workflows to communicate results. Correlate spectroscopic signatures with material properties, process conditions, surface states, and defect behavior while colla