application security engineer, ai security

software engineer

ai engineer

ai security engineer Jobs in San Francisco

ai security engineer

ai/generative ai engineer Jobs in San Francisco

ai/generative ai engineer

application security engineer, ai security Jobs in San Francisco

big data engineer

Uber

<div>
 
 About The Role
 
 
 
 The Growth and Marketing Platform Data Team is looking for a highly skilled and passionate Data Engineer to build and scale Uber's data infrastructure. In this role, you'll develop high-performance data pipelines, real-time streaming systems, and robust data architectures that power Uber's growth and marketing initiatives.
 
 
 You'll collaborate with Product Managers, Data Scientists, Data Platform Engineers, and Marketing Operations to design scalable, efficient, and reliable data solutions that drive business impact. This is a highly visible and impactful role for someone who thrives on data at scale, technical leadership, and solving ambiguous problems with clarity and precision.
 
 
 
 What You Will Do
 
 
 
 <ul>
 <li>
 Design, develop, and maintain scalable data pipelines and backend services for processing large-scale web event analytics.
 </li>
 <li>
 Lead the development of core data infrastructure, ensuring high availability, performance, and reliability.
 </li>
 <li>
 Solve complex challenges at the intersection of low latency, high correctness, and full determinism.
 </li>
 <li>
 Architect and optimize data models, ETL/ELT workflows, and distributed data processing frameworks.
 </li>
 <li>
 Participate in code reviews, mentor junior engineers, and enforce best practices in data engineering.
 </li>
 <li>
 Diagnose and resolve data quality issues, ensuring accuracy, efficiency, and security.
 
 
 </li>
 </ul>
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 4+ years of experience in data engineering or backend software development.
 </li>
 <li>
 Proficiency in Python, SQL, Java, or Scala for data pipeline development.
 </li>
 <li>
 Proficiency in Big Data frameworks (e.g., Spark, Flink, Presto, MapReduce) and distributed computing.
 </li>
 <li>
 Data warehouse and Data Modeling experience
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in Web and SEO Analytics
 </li>
 <li>
 Experience in Marketing Technologies
 </li>
 <li>
 Designing and executing on Real-time and Near Real-time Systems
 
 
 </li>
 </ul>
 For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits., For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
</div>

Data Engineer - Growth and Marketing Platform

Cognition

<div><h2 class="jobSectionHeader">We are an applied AI lab building end-to-end software agents.</h2>
We're the makers of Devin, the first AI software engineer, and Windsurf, the AI-native IDE. Together, they represent our vision for collaborative AI teammates that enable engineers to focus on more interesting problems and empower teams to strive for more ambitious goals.
Our team is small and talent-dense. Among our founding team, we have world-class competitive programmers, former founders, and leaders from companies at the cutting edge of AI including Scale AI, Palantir, Cursor, Waymo, Tesla, Lunchclub, Modal, Google DeepMind, and Nuro.
Building Devin and Windsurf is just the first step&mdash;our hardest challenges still lie ahead. If you&rsquo;re excited to solve some of the world&rsquo;s biggest problems and build AI that can reason on real-world tasks, apply to join us.<h2 class="jobSectionHeader">
About the Role</h2>
We&rsquo;re hiring a Data Engineer to help own our data stack &mdash; from database architecture and pipelines to integrations and reporting. You&rsquo;ll design and maintain the systems that keep our data reliable, accessible, and actionable across the Finance and Accounting organization.
In this role you will:<ul><li>
Design and manage database architecture and data models with a focus on finance and accounting use cases</li><li>
Build and maintain ETL/ELT pipelines and orchestration workflows</li><li>
Create and manage data integrations across internal and external financial systems</li><li>
Partner with Finance and Accounting teams to build auditable, automated reporting systems, dashboards, and datasets</li><li>
Support close processes, FP&amp;A workflows, and revenue reporting through scalable data infrastructure</li><li>
Own business reporting: datasets, dashboards, metrics, and self-serve analytics</li><li>
Ensure data quality, observability, governance, and documentation</li></ul>
Requirements for the role:<ul><li>
5+ years in a data engineering, analytics engineering, or a full-stack data role</li><li>
Expert SQL and strong Python (or R)</li><li>
Experience with data modeling, warehouse architecture, and BI-oriented schema design</li><li>
Hands-on experience with ETL/ELT tools (dbt, Airflow, Dagster, etc.)</li><li>
Experience building or maintaining BI reporting (Metabase a plus)</li><li>
Proven track record collaborating with finance stakeholders to deliver impactful solutions</li><li>
Experience with FP&amp;A processes, close workflows, and financial reporting</li><li>
Familiarity with GAAP vs. non-GAAP reporting and revenue recognition concepts</li><li>
Based in SF and willing to be in office 5 days a week</li></ul></div>

Data Engineer - Finance

Medeloop

<div><h2 class="jobSectionHeader">The Role</h2>

This is a full-ownership data engineering role at the center of Medeloop's AI platform. You won't be maintaining pipelines someone else built, you'll be architecting the data backbone that powers AI agents doing real operations at scale. You'll work directly with data scientists, AI engineers, and product teams to turn raw, complex healthcare data into the clean, structured, semantically-rich foundation our AI scientists depend on. Your work shows up in customer products and research outcomes, not internal dashboards that no one reads.Candidates who currently perform these tasks exclusively through manual processes are unlikely to be suitable for this role. We require an individual who has already adopted and integrated AI techniques to enhance operational velocity, rather than one who is contemplating future experimentation.If you want to build something that genuinely changes how medical research gets done, this is the role.
<h2 class="jobSectionHeader">
What You'll Own</h2>
<ul><li>The healthcare data lake: curating, extending, and evolving it through new concepts, derived variables, and data models that directly inform our AI engines and customer products</li>
<li>AI-native data workflows: designing and operating AI-powered pipelines (using tools like Claude Code and agent frameworks) to automate harmonization, cleaning, quality checks, and summarization at scale</li>
<li>NLP and semantic infrastructure: building pipelines for entity extraction, concept normalization, embedding-based retrieval, and semantic search that power the AI Scientist platform</li>
<li>Novel data extraction approaches: experimenting with and building new methodologies for working with unstructured clinical data, not just applying existing playbooks</li>
<li>Research-grade data products: delivering analytical samples, cohorts, and final datasets that withstand scientific scrutiny and are actively used by researchers and customers</li>
<li>Data governance and observability protocols: including access controls, PHI/PII handling, data classification, compliance, monitoring, alerting, data freshness, and comprehensive documentation to enable self-service capabilities.</li>
</ul><h2 class="jobSectionHeader">What We're Looking For</h2>
<ul><li>3+ years of relevant data engineering or data management within an analytics-driven organization, with end-to-end ownership from raw ingestion to final data product</li>
<li>Deep hands-on experience with healthcare CDMs (OMOP, FHIR, PCORnet) &mdash; designing or extending them, not just querying</li>
<li>Knowledge of medical ontologies: UMLS, SNOMED CT, RxNorm</li>
<li>Experience with big data, data pipelines and tooling that support retrieval-augmented generation (RAG), vector integrations, embedding workflows, and other AI/ML workloads. Experience in big data tooling such as Spark, Iceberg, EMR</li>
<li>Fluent in Python and SQL; comfortable across structured and unstructured data</li>
<li>Proven NLP experience: semantic search, entity recognition, concept normalization, embedding pipelines</li>
<li>Strong grasp of inferential statistics and cohort methodology to be a real partner to data scientists and customers (as part of onboarding)</li>
<li>Experience contributing to an AI/ML product, especially in automated research or scientific discovery</li>
<li>Experience mentoring other engineers and providing technical leadership</li>
</ul><h2 class="jobSectionHeader">Bonus Points</h2>
<ul><li>Multi-cloud experience (AWS, Azure, GCP)</li>
<li>Authorship or contribution to peer-reviewed publications or technical reports</li>
</ul><h2 class="jobSectionHeader">Why Medeloop</h2>
<ul><li>Ownership from day one: small team, high-trust, no layers between your work and its impact</li>
<li>Technically ambitious: you'll build AI-powered workflows, not just support them</li>
<li>Real-world stakes: your work accelerates drug development, addresses health equity, and improves clinical research for institutions that matter</li>
<li>Strong foundation: Series A, top-tier investors, and a data asset (200M+ patient records) that most companies spend years trying to build</li></ul></div>

Senior AI Data Engineer– Agentic Healthcare Platform

HappyRobot

<div>
 
 About HappyRobot
 
 
 
 HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate - they make decisions, take action, and run operations autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by a16z and Base10 with over $60M raised, we power critical operations for global enterprises worldwide.
 
 
 Our platform is battle-tested in the most demanding environments - where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto.
 
 
 
 About The Role
 
 
 
 <ul>
 <li>
 Build foundational data products, dashboards and tools to enable self-serve analytics to scale across the company.
 </li>
 <li>
 Develop insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company.
 </li>
 <li>
 Build and maintain robust data pipelines and models to ensure data quality.
 </li>
 <li>
 Partner with Product, Engineering, and Design teams to inform decisions.
 </li>
 <li>
 Translate complex data into clear, actionable insights for product teams.
 </li>
 <li>
 Love working with data. Love making product better. Love finding the story behind the numbers.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Define, build, and maintain product metrics, dashboards, and pipelines.
 </li>
 <li>
 Write SQL and Python code to extract, transform, and analyze data.
 </li>
 <li>
 Design and run experiments (A/B tests) to support product development.
 </li>
 <li>
 Proactively explore data to identify product opportunities and insights.
 </li>
 <li>
 Collaborate with cross-functional teams to ensure data-driven decisions.
 </li>
 <li>
 Ensure data quality, reliability, and documentation across analytics efforts.
 
 
 </li>
 </ul>
 
 Must Have
 
 
 
 <ul>
 <li>
 3+ years of experience as an Analytics Data Engineer or similar Data Science &amp; Analytics roles.
 </li>
 <li>
 Strong SQL and data engineering skills to transform data into accurate, clean data models (e.g., dbt, Airflow, data warehouses).
 </li>
 <li>
 Proficiency in Python for data analysis and modeling.
 </li>
 <li>
 Excellent communication skills: able to explain complex data insights clearly.
 </li>
 <li>
 Curious, collaborative, and driven to make an impact in a fast-paced environment.
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience in B2B SaaS or AI/ML products.
 </li>
 <li>
 Familiarity with product analytics tools (e.g., Mixpanel, Amplitude).
 </li>
 <li>
 Exposure to machine learning concepts or AI-powered systems.
 
 
 </li>
 </ul>
 
 Why join us?
 
 
 
 <ul>
 <li>
 Opportunity to work at a high-growth AI startup, backed by top investors.
 </li>
 <li>
 Rapidly growing and backed by top investors including a16z, Y Combinator, and Base10.
 </li>
 <li>
 Ownership &amp; Autonomy - Take full ownership of projects and ship fast.
 </li>
 <li>
 Top-Tier Compensation - Competitive salary + equity in a high-growth startup.
 </li>
 <li>
 Comprehensive Benefits - Healthcare, dental, vision coverage.
 </li>
 <li>
 Work With the Best - Join a world-class team of engineers and builders.
 
 
 </li>
 </ul>
 
 Our Operating Principles
 
 
 
 
 
 Extreme Ownership
 
 
 
 
 We take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting &mdash; if something needs fixing, we own it and make it better. This means stepping up, even when it&rsquo;s not &ldquo;your job.&rdquo; If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We don&rsquo;t wait for someone else to solve it &mdash; we lead with accountability and expect the same from those around us.
 
 
 
 
 Craftsmanship
 
 
 
 
 Putting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for &ldquo;just fine.&rdquo; We sweat the details because details compound. Whether it&rsquo;s a product feature, an internal doc, or a sales call &mdash; we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build &mdash; even when nobody&rsquo;s watching.
 
 
 
 
 We are &ldquo;majos&rdquo;
 
 
 
 
 Be friendly &amp; have fun with your coworkers. Always be genuine &amp; honest, but kind. &ldquo;Majo&rdquo; is our way of saying: be a good human. Be approachable, helpful, and warm. We&rsquo;re building something ambitious, and it&rsquo;s easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego.
 
 
 
 
 Urgency with Focus
 
 
 
 
 Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. We&rsquo;re running a high-speed marathon &mdash; not a sprint with no strategy.
 
 
 
 
 Talent Density and Meritocracy
 
 
 
 
 Hire only people who can raise the average; &lsquo;exceptional performance is the passing grade.&rsquo; Ability trumps seniority. We believe the best teams are built on talent density &mdash; every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players &mdash; that&rsquo;s how we win.
 
 
 
 
 First-Principles Thinking
 
 
 
 
 Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We don&rsquo;t copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. It&rsquo;s how we build what others think is impossible.
 
 
 
 The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller.
 
 
 
 
 By sending us your CV, you consent to the processing of your personal data for the purpose of evaluating and selecting you as a candidate for the position. Your personal data will be treated confidentially and will only be used for the recruitment process of the selected job offer.
 
 
 
 
 In relation to the period of conservation of your personal data, these will be eliminated after three months of inactivity in compliance with the GDPR and legislation on the protection of personal data.
 
 
 
 
 If you wish to exercise your rights of access, rectification, deletion, portability or opposition in relation to your personal data, you can do so through security@happyrobot.ai subject to the GDPR.
 
 
 
 
 For more information, visit
 
 
 https://www.happyrobot.ai/privacy-policy
 
 
 
 
 By submitting your request, you confirm that you have read and understood this clause and that you agree to the processing of your personal data as described.
 
</div>

Data Engineer

Embedding VC

<div><h3 class="jobSectionHeader">About OpenArt</h3>
OpenArt is an AI Storytelling and Visual Creation Platform used by millions worldwide. We&rsquo;re building the next generation of creative tools powered by cutting-edge AI, enabling anyone to create videos, visuals, characters, and stories with unprecedented speed and imagination. We believe the future of creativity is AI-native, and we&rsquo;re shaping that future.<h3 class="jobSectionHeader">
Why Join OpenArt</h3><ul><li>
Own the measurement and attribution layer of a fast-scaling AI company.</li><li>
Direct impact on growth &mdash; your work drives acquisition efficiency and revenue.</li><li>
Work across product, marketing, and data &mdash; highly cross-functional role.</li><li>
Build from 0 1 &mdash; define how we track, attribute, and optimize growth.
High ownership, low process, fast iteration environment.</li><li>
7&ndash;10X revenue growth over the past 2 years &mdash; now scaling growth infrastructure.</li></ul><h3 class="jobSectionHeader">
About the Role</h3>
We&rsquo;re looking for a Growth Data Engineer to build and own OpenArt&rsquo;s marketing data and attribution systems, ensuring that all acquisition and lifecycle efforts are accurately measured and optimized.
This role sits at the intersection of data engineering, marketing tech, and analytics &mdash; focused on making sure that data flows reliably between product, warehouse, CRM, and ad platforms.
You will be responsible for ensuring that every marketing dollar is measurable, attributable, and optimizable &mdash; from first touch to revenue.<h3 class="jobSectionHeader">
What You&rsquo;ll Do</h3><ul><li>
Build and maintain marketing attribution systems (UTM tracking, user journey, conversion mapping)</li><li>
Implement and manage 1st-party data passback to ad platforms (e.g., conversions, revenue, LTV signals)</li><li>
Configure and maintain tracking infrastructure:<ul><li>
GTM (client + server-side)</li><li>
Google Ads (Enhanced Conversions)</li><li>
Meta Pixel + Conversions API</li><li>
LinkedIn, TikTok, and other ad platforms</li></ul></li><li>
Set up and maintain conversion events and schemas across platforms</li><li>
Ensure consistent event definitions and naming across product, CRM, and ad platforms</li><li>
Build and manage audience sync pipelines</li><li>
Integrate CRM and warehouse data into ad platforms for optimization (offline conversions, lead stages, revenue)</li><li>
Operationalize new marketing experiments (UTMs, tracking parameters, campaign setup)</li><li>
Debug and resolve tracking and attribution discrepancies across systems (e.g., Ads vs CRM vs warehouse)</li><li>
Build and validate marketing and pipeline dashboards, ensuring data accuracy and consistency</li><li>
Implement privacy-safe tracking practices (Consent Mode, CMP integrations)</li><li>
Partner closely with growth, product, and data teams to ensure measurement supports decision-making</li></ul><h3 class="jobSectionHeader">
What We&rsquo;re Looking For</h3>
Core Requirements<ul><li>
3&ndash;5 years of experience in growth data, marketing data engineering, or analytics engineering</li><li>
Strong hands-on experience with:<ul><li>
GTM, pixels, conversion APIs</li><li>
Ad platforms (Google Ads, Meta, etc.)</li></ul></li><li>
Experience implementing conversion tracking and attribution systems</li><li>
Experience sending offline conversions / LTV signals back to ad platforms</li><li>
Familiarity with data pipelines and warehouse concepts (BigQuery, SQL, ETL/ELT)</li><li>
Strong SQL skills; comfortable working with data directly</li><li>
Strong debugging skills &mdash; able to systematically investigate and resolve data discrepancies</li><li>
Comfortable working cross-functionally with marketing, product, and data teams</li><li>
High ownership, fast execution, and strong attention to detail</li></ul>
Nice to Have<ul><li>
Experience supporting performance marketing teams</li><li>
Familiarity with:<ul><li>
Attribution models (last-click, MTA, probabilistic vs deterministic)</li><li>
Privacy frameworks (SKAN, ATT, Privacy Sandbox)</li></ul></li><li>
Experience with mobile attribution tools (AppsFlyer, Adjust, Branch)</li><li>
Experience with experimentation and A/B testing frameworks</li><li>
Experience in consumer product, marketplaces, or e-commerce</li><li>
Basic Python or scripting for automation</li></ul><h3 class="jobSectionHeader">
Tech Stack You&rsquo;ll Work With</h3>
GTM, Google Ads, Meta Ads, TikTok Ads, BigQuery, Metabase, Amplitude, Stripe, SQL, GCP<h3 class="jobSectionHeader">
Compensation</h3><ul><li>
Competitive base salary and bonus program</li><li>
Equity &mdash; meaningful ownership in what you build</li><li>
High autonomy, high growth environment</li></ul><h3 class="jobSectionHeader">
Work Setup</h3><ul><li>
Bay Area preferred (hybrid allowed)</li><li>
Visa sponsorship available</li><li>
We&rsquo;ll consider remote</li></ul></div>

Growth Data Engineer

OpenAI

<div>
 
 About The Team
 
 
 
 OpenAI&rsquo;s mission is to ensure AI benefits all of humanity. ChatGPT for Work supports that mission by helping more people access real leverage from AI in their day-to-day jobs&mdash;so they can spend less time on busywork and coordination, and more time on the work that&rsquo;s meaningful and additive. We&rsquo;re building an AI-native workspace where AI acts as a superassistant for everyday tasks and a coworker you can hand work off to&mdash;then review, edit, and approve with confidence.
 
 
 And we&rsquo;re doing it in a way organizations can trust, by grounding experiences in the right company context and systems safely and reliably.
 
 
 
 About The Role
 
 
 
 As the Data Scientist for ChatGPT for Work, you&rsquo;ll shape product strategy through data: uncover the user problems most worth solving, form sharp hypotheses about what will move team and business outcomes, and influence what we build next by presenting compelling recommendations grounded in rigorous evidence. You&rsquo;ll be the DRI for the Work
 
 insight &rarr; strategy &rarr; experiment &rarr; decision
 
 loop&mdash;defining what &ldquo;success&rdquo; means for teams, pinpointing the highest-leverage adoption and retention bottlenecks, and turning signals into clear product direction.
 
 
 You&rsquo;ll partner closely with Product, Engineering, Research, and Finance to ensure our metrics are trusted, our experimentation is rigorous, and our insights turn into shipped improvements.
 
 
 This role is based in San Francisco. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Own the core KPI framework for ChatGPT for Work, spanning onboarding, activation, engagement, retention, and expansion, as well as quality/trust guardrails.
 </li>
 <li>
 Build end-to-end funnels that identify where individuals and teams succeed or get stuck, from first workspace setup through repeat usage and long-term team adoption and value creation.
 </li>
 <li>
 Define and operationalize &ldquo;time-to-value&rdquo; and collaboration loop metrics, and connect them to business outcomes.
 </li>
 <li>
 Design and evaluate experiments and rollouts to quantify the impact of product changes across key Work surfaces and flows.
 </li>
 <li>
 Partner with product and engineering teams to improve instrumentation, data quality, and metric definitions so decisions are fast and correct.
 </li>
 <li>
 Translate complex analysis into clear, compelling insights that shape product strategy and roadmap decisions.
 </li>
 <li>
 Help establish data science standards and best practices for measuring human&ndash;AI collaboration and AI-native work outcomes.
 </li>
 <li>
 Partner with other data scientists across the company to share learnings and raise the bar on measurement, experimentation, and decision-making.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You Have
 
 
 
 <ul>
 <li>
 10+ years in data science / analytics in in high-velocity product environments
 </li>
 <li>
 Direct experience working on B2B products (SaaS, collaboration/workspace, developer tools, or enterprise)
 </li>
 <li>
 Expert SQL + strong Python
 </li>
 <li>
 Strong experimentation + causal inference judgment (incl. when clean A/B tests aren&rsquo;t feasible)
 </li>
 <li>
 Strong product sense/taste: can turn messy signals into crisp hypotheses and roadmap direction
 </li>
 <li>
 Proven ability to inspire and influence PM/Eng/Design + leadership through data storytelling
 </li>
 <li>
 Autonomous operator who sets the insights/measurement agenda
 </li>
 <li>
 Excellent executive communication; thrives in ambiguous, fast-moving environments
 </li>
 <li>
 AI-native operator (non-negotiable): &ldquo;super AI-pilled&rdquo;&mdash;first to adopt new AI tools, uses them daily to increase throughput, and turns them into durable org workflows
 
 
 </li>
 </ul>
 
 Nice-to-haves
 
 
 
 <ul>
 <li>
 Experience with agentic and/or AI-native B2B products (agents, copilots, workflow automation, AI collaboration)
 </li>
 <li>
 Experience measuring AI product quality, trust, and human-AI interaction signals
 </li>
 <li>
 Familiarity with enterprise admin/security constraints and how they shape adoption
 </li>
 <li>
 Experience with B2B PLG growth loops and monetization/seat expansion dynamics
 
 
 </li>
 </ul>
 
 Why it matters
 
 
 
 Work is one of the biggest places AI can improve people&rsquo;s lives. If we get ChatGPT for Work right, we help individuals and teams spend less time on busywork and coordination and more time on the work that&rsquo;s meaningful and additive&mdash;making better decisions, moving faster, and producing higher-quality outcomes. This role matters because the way we measure, learn, and iterate will determine whether AI becomes a genuinely trusted superassistant and coworker for everyday knowledge work, at scale.
 
 
 
 About OpenAI
 
 
 
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
 
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
 
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 
 
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
 
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 
 
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 
 
 OpenAI Global Applicant Privacy Policy
 
 
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
</div>

Data Scientist, ChatGPT for Work

Capital One

<div>Distinguished Software Data Engineer
As a Distinguished Engineer at Capital One, you will be a part of a community of technical experts working to define the future of banking in the cloud.
You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Distinguished Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while driving towards strong technology solutions.
At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence, and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring internal talent and actively recruiting to keep building our community.
Distinguished Engineers are individual contributors who strive to be diverse in thought so we holistically visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next generation technology solutions. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other material to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization.
We expect our Distinguished Engineers to be<ul><li>
Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices.</li><li>
Visionaries who challenge the status quo, collaborating on Capital One&rsquo;s toughest issues, to deliver on business needs that directly impact the lives of our customers and associates.</li><li>
Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community.</li><li>
Evangelists, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled</li></ul>
In this role, you will work with our Enterprise Data Platform team to drive design and architecture of Capital One&rsquo;s mission critical Data Platforms.<ul><li>
You will define and execute a bold technical strategy for a unified Data Product architecture, engineering high-scale solutions for standardized, well-governed data creation that serves as the bedrock for enterprise-wide AI readiness. By modernizing our foundational Business Data Catalog, you will transform how the organization discovers and consumes data, turning fragmented datasets into high-fidelity, machine-ready assets.</li><li>
You will act as the bridge between deep engineering and business impact, to institutionalize and drive the adoption of rigorous data standardization practices, ensuring that our data consumption layer becomes a competitive engine that enables the enterprise to innovate with speed and precision.</li><li>
You are a visionary builder who balances high-level architecture with &quot;hands-on-keyboard&quot; execution, designing resilient, multi-tenant distributed systems and event-driven patterns that redefine enterprise scale.</li><li>
As the authoritative expert in data consumption, you don't just advise&mdash;you build the proof-of-concepts and exploratory analyses that bridge the gap between abstract tech strategy and mission-critical, production-grade solutions.</li><li>
Beyond the code, you are a catalyst for growth, mentoring the next generation of world-class engineers and championing a culture of inclusive excellence and inner-sourcing.</li><li>
You command the technical depth to influence executive strategy and the hands-on credibility to lead the enterprise-wide shift toward modern, AI-ready technologies.</li></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 7 years of experience in data engineering</li><li>
At least 3 years of experience in data architecture</li><li>
At least 2 years of experience building applications in AWS</li></ul>
Preferred Qualifications:<ul><li>
Masters&rsquo; Degree</li><li>
9+ years of experience in data engineering</li><li>
3+ years of data modeling experience</li><li>
2+ years of experience with ontology standards for defining a domain</li><li>
2+ years of experience using Python, SQL or Scala</li><li>
1+ year of experience deploying machine learning models</li><li>
3+ years of experience implementing big data processing solutions on AWS</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $269,100 - $307,200 for Distinguished Data Engineer 

San Francisco, CA: $293,600 - $335,100 for Distinguished Data Engineer 

San Jose, CA: $293,600 - $335,100 for Distinguished Data Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>

Distinguished Software Data Engineer

Explore 209+ Big data engineer in San Francisco this April. Find roles across top companies and apply now to boost your career.