data scientist

software engineer

advisor - scientific data engineer Jobs in San Francisco

advisor - scientific data engineer

ai engineer, ai & data platforms (aidp) Jobs in San Francisco

ai engineer, ai & data platforms (aidp)

ai engineering lead Jobs in San Francisco

ai engineering lead

senior data scientist

Data Scientist, Product Analytics

Samba TV

<div>
 <p>
  <strong>
   Samba is a media intelligence company. We know what the world is watching, reading, and thinking about &amp;mdash; in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it&rsquo;s the most interesting data asset on the planet, because it&rsquo;s the most culturally relevant.&nbsp;
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
  <p>
   <strong>
    <span>
     ABOUT THE ROLE
    </span>
   </strong>
  </p>
  <br/>
  <p>
   <span>
    We are looking for a hands-on Data Scientist to own and deliver complex measurement science and modeling work at the core of our measurement and audience sciences products.&nbsp;
   </span>
  </p>
  <br/>
  <p>
   <span>
    The role requires a deep, first-principles understanding of data science and machine learning &amp;mdash; not just the ability to apply libraries, but the ability to reason clearly about model behavior, articulate trade-offs between approaches, and make defensible methodological decisions under ambiguity. This is emphatically a coding role &amp;mdash; you will spend the majority of your time writing production-quality Python, building and evaluating models on large-scale viewership and web data, and delivering end-to-end ML solutions.
   </span>
  </p>
  <br/>
  <p>
   <span>
    You will work closely with Data Engineering, Product, and go-to-market teams.
   </span>
  </p>
  <br/>
 </p>
 <p>
  <p>
   <br/>
  </p>
  <strong>
   WHAT YOU'LL DO
  </strong>
  <br/>
  <ul>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Write and own production-quality Python code end-to-end &amp;mdash; well-structured, tested, documented, and built to last; PySpark proficiency is essential for working with Samba's billion-row viewership datasets
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Design, build, and deploy measurement models and statistical frameworks that power Samba&rsquo;s campaign measurement, reach/frequency estimation, and cross-platform attribution products
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Apply the right statistical and ML technique to the right problem &amp;mdash; drawing from hierarchical models, Bayesian inference, gradient boosting, regularized regression, causal ML, and probabilistic record linkage &amp;mdash; and clearly articulate the reasoning behind your choices
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Build and evaluate multi-touch and multi-channel attribution models; apply Causal ML methods &amp;mdash; counterfactual modeling, meta-learners (S-learner, T-learner, X-learner), and heterogeneous treatment effect estimation &amp;mdash; to advertising and viewership measurement problems
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Partner with Data Engineering to define data requirements, validate pipelines, and ensure model inputs are reliable, scalable, and production-ready
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Lead technical design reviews and contribute meaningfully to architecture decisions across the Data Science team
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Mentor junior Data Scientists through code review, pairing, and structured technical feedback &amp;mdash; raising the team's technical floor
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Communicate measurement methodologies and findings clearly to technical and non-technical audiences, including senior leadership and external clients
     </span>
    </p>
    <br/>
   </li>
   <br/>
  </ul>
  <br/>
  <p>
   <br/>
  </p>
  <strong>
   WHO ARE YOU
  </strong>
  <br/>
  <ul>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      5-7 years of professional data science experience &amp;mdash; hands-on, delivery-focused, and measurable in shipped models and production systems
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Expert-level Python &amp;mdash; clean, modular, testable, production-ready code is your standard, not your aspiration
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Advanced PySpark and Databricks &amp;mdash; comfortable building and optimizing data pipelines and ML workflows on billion-row datasets
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Deep, first-principles command of statistics and ML &amp;mdash; you can explain from the ground up how these models work and you apply this understanding to make better modeling decisions
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Solid grasp of experimental design &amp;mdash; A/B testing, randomization, power analysis, and the conditions under which observational causal inference is appropriate
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Fluent in the full ML lifecycle: feature engineering, model evaluation, deployment pipelines, drift monitoring, and iterative improvement in production
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Hands-on experience with uplift modeling, synthetic control, difference-in-differences, or propensity-based approaches applied to advertising or media outcomes
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Strong ownership mindset &amp;mdash; you drive projects independently and are comfortable owning your models from data exploration through production delivery, with minimal hand-holding.
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Clear communicator &amp;mdash; able to translate statistical reasoning and model behavior into language that drives decisions with product, engineering, and leadership
     </span>
    </p>
    <br/>
   </li>
   <br/>
  </ul>
  <br/>
  <br/>
  <ul>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Experience with multi-touch attribution (MTA) or multi-channel attribution modeling &amp;mdash; understanding of the limitations of rule-based approaches and the methodological trade-offs of data-driven alternatives
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Hands-on experience with Causal ML methods &amp;mdash; counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation &amp;mdash; applied to advertising or media measurement outcomes
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Direct exposure to TV or digital viewership data &amp;mdash; ACR signals, STB data, viewership panels, or cross-platform measurement (linear + CTV/OTT)
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Familiarity with the measurement
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      t vendor landscape (Nielsen, Comscore, VideoAmp, iSpot) and industry standards (MRC, GRP/TRP frameworks)
     </span>
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <span>
      Advanced degree (MS or PhD) in Statistics, Mathematics, Computer Science, or a related quantitative field &amp;mdash; or equivalent depth demonstrated through work
     </span>
    </p>
    <br/>
   </li>
   <br/>
  </ul>
  <br/>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <br/>
 <p>
  <strong>
   Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.&nbsp;&nbsp;We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.
  </strong>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <span>
   Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law.
  </span>
  <strong>
   For further details, please see Samba's
  </strong>
  <strong>
   Applicant Privacy Policy
  </strong>
  <strong>
   .
  </strong>
  <strong>
   For residents of the EU , Samba Inc. is the data controller.
  </strong>
 </p>
 <br/>
 <p>
  We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
 </p>
 <br/>
 <br/>
 Samba expects to offer a base salary between
 <strong>
  $150,000 - $180,000 USD
 </strong>
 per year for roles to be performed in San Francisco or California; actual base salary offered will depend on various factors including but not limited to location, experience, and performance. Base salary is just one component of Samba's total compensation package for employees. Other rewards may include bonuses, short-term incentives and long-term incentives. In addition, Samba provides health insurance, wellness offerings, life and disability insurance, a retirement savings plan, paid holidays and paid time off (PTO), and other employee benefits.
</div>


Data Scientist

Shipt

<div>
 <strong>
  Impact
  <br/>
  <br/>
 </strong>
 As a Data Scientist specializing in geospatial intelligence, you will help power the next generation of final-mile logistics. This role will develop advanced models and data systems that leverage location, routing, traffic, and spatial signals to improve delivery success, reduce operational costs, and create a better experience for customers and drivers.
 <br/>
 <br/>
 In this role you will work with large-scale GPS traces, mapping data and geospatial datasets. You will collaborate with product ,managers, logistic operators and software engineers to turn models into real-world systems. You will design experiments and translate complex geospatial insights into actionable operational decisions.
 <br/>
 <br/>
 <strong>
  <strong>
   What You&rsquo;ll Need to Be Successful
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   MS or PhD in Statistics, Applied Mathematics, Computer Science, or other quantitative fields
  </li>
  <li>
   2+ years of experience with geospatial data (ex. GPS traces, spatial indexing systems, or routing systems)
  </li>
  <li>
   Strong understanding of predictive modeling, feature engineering, experimentation and causal inference
  </li>
  <li>
   Strong Python skills with experience in libraries such as: pandas, scikit-learn, PyTorch or TensorFlow
  </li>
  <li>
   Ability to work with large datasets and distributed systems (ex. Spark, BigQuery, Snowflake, etc.)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Pay Range: $76,100- $130,000
  <br/>
  <br/>
 </strong>
 <strong>
  <em>
   Please note that the salary range above is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location.
   <br/>
   <br/>
  </em>
 </strong>
 <strong>
  Skills &amp; Education
  <br/>
  <br/>
 </strong>
 This list includes key skills used in this job but is not inclusive of all skills needed for the role. Please see any required education below.
 <br/>
 <br/>
 Data Science, Geospatial Data, Geospatial Modeling, Python (Programming Language)
 <br/>
 <br/>
 Bachelor's Degree or equivalent experience&emsp14;| Required
 <br/>
 <br/>
 <strong>
  Work Arrangement
  <br/>
  <br/>
 </strong>
 Shipt considers candidates located near a Shipt office or workspace in Birmingham, San Francisco, or Minneapolis to be hybrid, which means that they have the flexibility to work from home (with leader approval) or at a Shipt office in order to facilitate the ability to innovate, collaborate, and spark team connections. In-office expectations will vary by role and leader. Certain roles may require in-office presence on a full-time basis. Please work with your recruiter to learn more about the classification of this role.
 <br/>
 <br/>
 <strong>
  About Shipt
  <br/>
  <br/>
 </strong>
 Shipt is a retail tech company that connects people to reliable, high-quality delivery with a personal touch. Shipt connects customers to the things they want from the stores they love, retail businesses to more satisfied customers, and workers to new earning opportunities.
 <br/>
 <br/>
 At Shipt, we aim to put our team first to boost a sense of belonging, spark opportunities for growth, provide unique benefits and commit to giving back to our communities in ways that make life better, both personally and professionally. We understand that our service, our culture, and our connection to our communities are only made better by every single person who shows up to work here every day.  Learn More.
 <br/>
 <br/>
 Shipt is an independently operated, wholly owned subsidiary of Target Corporation and available in more than 5,000 U.S. cities. Shipt was founded and is headquartered in Birmingham, Alabama. For more information, please visit Shipt&rsquo;s company site at Shipt.com.
 <br/>
 <br/>
 <em>
  We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or any other characteristic protected by law.
  <br/>
  <br/>
 </em>
 <em>
  Please inform your recruiting contact upon initial connection if you need a reasonable accommodation. If you need assistance filling out a job application, please complete this form.
  <br/>
  <br/>
  For technical interviews, Shipt uses an online coding platform. In the event you may need a reasonable accommodation to use the online coding platform, please connect with your recruiter.
  <br/>
  <br/>
 </em>
 <em>
  Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
  <br/>
  <br/>
 </em>
 <em>
  Employees (and eligible family members) are covered by medical, dental, vision and more. Employees may enroll in our company&rsquo;s 401k plan. Employees will also be eligible to receive discretionary vacation for exempt team members, paid holidays throughout the calendar year and paid sick leave. Other compensation includes eligibility for an annual bonus and the potential for restricted stock units based on role.
 </em>
</div>


Aircall

<div>
 Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We&rsquo;re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace.
 <br/>
 <br/>
 Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall&rsquo;s AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.
 <br/>
 <br/>
 Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We&rsquo;ve built a product customers love and a business that&rsquo;s scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines.
 <br/>
 <br/>
 At Aircall, you&rsquo;ll join a company in motion. We&rsquo;re ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth.
 <br/>
 <br/>
 <strong>
  How we work at Aircall:
 </strong>
 We&rsquo;re customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you&rsquo;ll feel at home here.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 The Data Engineering team at Aircall works on providing high-quality, reliable, and actionable data. As an AI-first data team, we are currently in a pivotal transition to build a robust semantic layer that will power our AI-first data platform, enabling analytics at speed and democratizing intelligent insights across the company. Some of the key problems we are currently solving include taking charge of data reliability, integrating new sources for raw data ingestion, and building sophisticated data models to power real-time dashboards and predictive analytics.
 <br/>
 <br/>
 In this role, you will be instrumental in building new datasets for high-impact use cases such as churn prediction and feature adoption, while owning the end-to-end reliability and scalability of our data pipelines. You will work closely with Product and GTM business teams, sitting at the heart of a larger data organization alongside Data Science, Analytics, and Applied Scientists to bridge the gap between raw data and AI-driven decision-making.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build and maintain core data infrastructure pieces that allow Aircall to support our many data use cases.
  </li>
  <li>
   Enhance the data stack, lineage monitoring and alerting to prevent incidents and improve data quality.
  </li>
  <li>
   Implement best practices for data management, storage and security to ensure data integrity and compliance with regulations.
  </li>
  <li>
   Own the core company data pipeline, responsible for converting business needs to efficient &amp; reliable data pipelines.
  </li>
  <li>
   Participate in code reviews to ensure code quality and share knowledge.
  </li>
  <li>
   Lead efforts to evaluate and integrate new technologies and tools to enhance our data infrastructure.
  </li>
  <li>
   Define and manage evolving data models and data schemas. Manage SLA for data sets that power our company metrics.
  </li>
  <li>
   Collaborate with applied scientists, data scientists, analysts and other business stakeholders to drive efficiencies for their work, supporting complex data processing, storage and orchestration
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  A little more about you:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree or higher in Computer Science, Engineering, or a related field.
  </li>
  <li>
   3+ years of experience in data engineering, with a strong focus on designing and building data pipelines and infrastructure.
  </li>
  <li>
   Proficient in SQL and Python, with the ability to translate complexity into efficient code.
  </li>
  <li>
   Experience with data workflow development and management tools (dbt, Airflow).
  </li>
  <li>
   Solid understanding of distributed computing principles and experience with cloud-based data platforms such as AWS, GCP, or Azure.
  </li>
  <li>
   Strong analytical and problem-solving skills, with the ability to effectively troubleshoot complex data issues.Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
  </li>
  <li>
   Prior experience designing AI-ready data semantic layer is a major plus, specifically for enabling low-latency, high-fidelity analytics at scale.
  </li>
  <li>
   Experience with data tooling, data governance, business intelligence and data privacy is a plus.
   <br/>
   <br/>
  </li>
 </ul>
 $130,000 - $200,000 a year
 <br/>
 <br/>
 This is not including equity and other benefits. The actual salary offered will carefully consider a wide range of factors, including your skills, qualifications, and experience.
 <br/>
 <br/>
 Why join us?
 <br/>
 <br/>
 🚀 Key moment to join Aircall in terms of growth and opportunities
 <br/>
 <br/>
 💆&zwj;&female;️ Our people matter, work-life balance is important at Aircall
 <br/>
 <br/>
 📚 Fast-learning environment, entrepreneurial and strong team spirit
 <br/>
 <br/>
 🌍 45+ Nationalities: cosmopolite &amp; multi-cultural mindset
 <br/>
 <br/>
 💵 Competitive salary package &amp; benefits
 <br/>
 <br/>
 🏨 Medical, dental, and vision insurance is 100% covered
 <br/>
 <br/>
 📈 401k plan with company matching!
 <br/>
 <br/>
 ✈️ Unlimited PTO &mdash; take the time you need to come to work feeling great!
 <br/>
 <br/>
 ⭐️ Wellness, commuter, and childcare reimbursements
 <br/>
 <br/>
 💚 Generous parental leave policy
 <br/>
 <br/>
 DE&amp;I Statement:
 <br/>
 <br/>
 At Aircall, we believe diversity, equity and inclusion &ndash; irrespective of origins, identity, background and orientations &ndash; are core to our journey.
 <br/>
 <br/>
 We pride ourselves on promoting active inclusion within our business to foster a strong sense of belonging for all. We&rsquo;re working to create a place filled with diverse people who can enrich and learn from one another. We&rsquo;re committed to ensuring that everyone not only has a seat at the table but is valued and respected at it by providing equal opportunities to develop and thrive.
 <br/>
 <br/>
 We will constantly challenge ourselves to make sure that we live up to our ambitions around diversity, equity and inclusion, and keep this conversation open. Above all else, we understand and acknowledge that we have work to do and much to learn.
 <br/>
 <br/>
 Want to know more about candidate privacy? Find our Candidate Privacy Notice here.
 <br/>
 <br/>
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>


Data Engineer/Senior Data Engineer, Data and Science

Autodesk

<div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p><b>Job Requisition ID #</b></p></div></div></div></div></div></div></div></div></div></div></div></div></div></div><div></div>
26WD98776<p></p><div><div><p><b>
Position Overview</b></p><p>
Autodesk is shaping the future of the Design and Make by building a global, high-throughput Product Data platform that powers design, collaboration, and lifecycle workflows across multiple domains. If you are a hands-on technologist who enjoys leading teams solving petabyte scale problems and building the next generation of knowledge retrieval systems, this may be an opportunity for you.</p></div><p></p><div><p><br>
Product Data is Autodesk's transactional data platform that manages Design and Make Data generated by millions of customers across three industries &ndash; Architecture, Engineering and Construction (AEC), Manufacturing (MFG) and Media &amp; Entertainment (M&amp;E). The platform is a collection of capabilities and highly scalable data services such as document management, fine grained permissions, stream processing, data pipelines, search, granular data management, and cross industry interoperability. We are also evolving our search capabilities to the next generation of Knowledge Representation and Retrieval systems with semantic search, GraphRAG and Context Graphs.</p></div><p></p><div><p><br>
Reporting to the VP Product Data, we are seeking a Senior Director of Data Architecture and Engineering to own the architectural vision of the overall data platform, while leading the engineering execution of our advanced knowledge retrieval systems. In this role you will lead a team of senior technical leaders (software architects, distinguished engineers) and engineering leaders to help scale and grow the platform. You will interface with architecture and engineering leaders across Autodesk to<i> </i>unify complex, historically fragmented design and make data across Autodesk&rsquo;s ecosystem into a coherent, scalable platform.</p></div><p></p><div><p><br>
The successful candidate is an experienced engineering leader with a passion for large-scale systems and building high-performing teams. They combine deep technical expertise, cutting edge knowledge of distributed real-time data management systems with innovative engineering practices, and leadership presence to drive alignment and execution across product, platform, and ecosystem teams.</p></div><p></p><div><p><br>
As this role oversees a global organization, you will work across multiple time zones and travel up to 15% for team offsites and internal and customer events. The role can be based in the US or Canada remote, hybrid, or in person in one of our offices.</p></div><p></p><div><p><br>
</p></div><div><p><b>Responsibilities</b></p></div><div><ul><li><p>
Lead the Architectural vision for the Product Data platform</p></li></ul></div><div><ul><li><p>
Drive complex architectural decisions and technology innovation in OLTP systems infrastructure</p></li></ul></div><div><ul><li><p>
Build and evolve the knowledge retrieval engineering organization to deliver predictable execution, high quality, and operational excellence</p></li></ul></div></div><div><div><ul><li><p>
Hire, mentor, and retain the next generation of engineering leaders</p></li></ul></div><div><ul><li><p>
Serve as a senior leader within the Product Data leadership team, shaping organizational strategy, prioritization, execution, and innovation across the portfolio</p></li></ul></div><div><ul><li><p>
Partner with product, platform, and ecosystem teams to drive adoption of the Product Data platform across Autodesk&rsquo;s product portfolio, influencing architecture and data standards across the company and taking ownership of critical cross-product initiatives</p></li></ul></div><div><ul><li><p>
Define the long-term evolution of Autodesk&rsquo;s domain data model and influence broader technical strategy around domain data, interoperability, and platform architecture</p></li></ul></div><div><ul><li><p>
Stay at the forefront of emerging technologies and engineering practices, identifying and driving adoption of innovations that materially improve platform capabilities and developer productivity</p></li></ul></div><p></p><div><p><b><br>
Minimum Qualifications</b></p></div><div><ul><li><p>
15+ years of software engineering experience, with 5+ years leading architects, managers and senior leaders across global teams</p></li></ul></div><div><ul><li><p>
Demonstrated ability to adopt and scale AI-driven engineering practices to accelerate delivery and improve developer effectiveness</p></li></ul></div><div><ul><li><p>
Proven track record of owning and delivering large-scale, complex systems or platforms with measurable business impact</p></li></ul></div><div><ul><li><p>
Experience building and scaling high-performing engineering organizations, including org design and leadership development</p></li></ul></div><div><ul><li><p>
Established history of driving operational excellence (quality, reliability, scalability, and execution predictability)</p></li></ul></div><div><ul><li><p>
Deep expertise in distributed systems, databases, cloud platforms, high-scale transactional environments, knowledge retrieval systems and modern software architecture patterns</p></li></ul></div><div><ul><li><p>
Exceptional communication and influencing skills, with the ability to align product, platform, external, and executive stakeholders</p></li></ul></div><div><ul><li><p>
Ability to understand complex business requirements and quickly and iteratively execute against them in a highly matrixed environment</p></li></ul></div><div><ul><li><p>
Systems thinker with a strong desire to understand how complex systems work</p></li></ul></div><p></p><div><p><b><br>
Preferred Qualifications</b></p></div><div><ul><li><p>
Experience building or leading domain-specific data platforms (e.g., AEC, BIM, GIS, manufacturing, or other complex object models)</p></li></ul></div><div><ul><li><p>
Experience with schema evolution, versioning, and backward compatibility in long-lived, large-scale systems</p></li></ul></div></div><div><div><ul><li><p>
Understanding of how operational product data interfaces with analytics, AI, and downstream data platforms</p></li></ul></div><div><ul><li><p>
Experience influencing industry standards, data interoperability frameworks, or open ecosystems</p></li></ul></div><div><ul><li><p>
Track record of driving platform adoption across large, federated organizations</p></li></ul></div><div><ul><li><p>
Strong grasp on object-oriented design principles and enterprise domain/data modeling</p></li></ul></div><div><ul><li><p>
Advanced degree in computer science, engineering, or related field</p></li></ul></div></div><p></p><div><div><div><div><div><div><div><p><b>
Learn More</b></p></div></div></div></div></div></div></div><p></p><p><b>
About Autodesk</b></p><p>
Welcome to Autodesk! Amazing things are created every day with our software &ndash; from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.</p><p></p><p>
We take great pride in our culture here at Autodesk &ndash; it&rsquo;s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.</p><p></p><p>
When you&rsquo;re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!</p><p></p><p><b>
Benefits</b></p><p>
From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/</p><p></p><div><div><div><div><div><div><div><p><b>
Salary transparency</b></p></div></div></div></div></div></div></div>
Salary is one part of Autodesk&rsquo;s competitive compensation package. For U.S.-based roles, we expect a starting base salary between $192,000 and $344,850. Offers are based on the candidate&rsquo;s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.<p></p><p><b>
Equal Employment Opportunity</b><b>
</b></p><p>At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.</p><p></p><p><b>
Diversity &amp; Belonging</b></p><p>
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging</p><p></p><p><b>
Are you an existing contractor or consultant with Autodesk?
</b></p><p>Please search for open jobs and apply internally (not on this external site).</p></div>

Senior Director, Data Architecture and Engineering

OpenAI

About the Team
<br><br>
The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely.
<br><br>
The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting.
<br><br>
About the Role
<br><br>
We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems.
<br><br>
You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity.
<br><br>
In This Role, You Will
<br><br>
Lead and grow a high-performing Trust & Safety Data Engineering team.
<br><br>
Define the roadmap and technical strategy for Trust & Safety data systems.
<br><br>
Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring.
<br><br>
Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting, evaluation, and production inputs.
<br><br>
Establish ownership, documentation, data quality standards, monitoring, and operational rigor for critical datasets and workflows.
<br><br>
Reduce dependence on sensitive raw logs by building structured alternatives with appropriate access controls, retention, deletion semantics, and governance.
<br><br>
Partner with Trust & Safety, Product, Policy, Privacy, Data Science, Engineering, and Data Platform on launch readiness, operational systems, and safety measurement.
<br><br>
Raise the bar for technical judgment, prioritization, communication, and execution in a fast-moving environment.
<br><br>
You Might Thrive in This Role If You
<br><br>
Have led data engineering teams that build and operate production data systems at scale.
<br><br>
Experience in trust and safety, integrity, abuse prevention, fraud, investigations, risk operations, safety systems, privacy, or adjacent domains.
<br><br>
Are deeply technical and comfortable with data architecture, modeling, pipelines, reliability, privacy, and operational tradeoffs.
<br><br>
Have experience with large-scale data systems such as Spark, Airflow or similar orchestration systems, distributed storage, batch/streaming pipelines, and modern warehouse patterns.
<br><br>
<b>Think of data as a product:</b> reliable, documented, governed, observable, discoverable, and designed for repeated use.
<br><br>
Can create clarity in ambiguous problem spaces and make principled tradeoffs quickly.
<br><br>
Have a strong track record partnering with senior stakeholders across engineering, data science, operations, policy, privacy, product, or executive teams.
<br><br>
Have hired, developed, and retained senior engineers.
<br><br>
Are motivated by building systems that make frontier AI products safer and more trustworthy.
<br><br>
Nice to Have
<br><br>
Experience supporting ML systems through feature engineering, training data, labels, model evaluation, or production model pipelines.
<br><br>
Experience with launch readiness, monitoring, alerting, incident response, semantic layers, metrics governance, or executive-facing reporting.
<br><br>
Workplace & Location
<br><br>
This role is based in our San Francisco HQ. We offer relocation assistance to new employees.
<br><br>
<b>Please note:</b> this role may involve work related to sensitive or concerning safety, abuse, fraud, or user-risk domains. Strong discretion, judgment, and resilience are essential.
<br><br>
About OpenAI
<br><br>
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.
<br><br>
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.
<br><br>
For additional information, please see
<br><br>
OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement
<br><br>
.
<br><br>
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.
<br><br>
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through
<br><br>
this form
<br><br>
. No response will be provided to inquiries unrelated to job posting compliance.
<br><br>
We are committed to providing reasonable accommodations to applicants with disabilities.
<br><br>
OpenAI Global Applicant Privacy Policy
<br><br>
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.
<br><br>
Compensation
<br><br>
$385K – $490K + Offers Equity

Technical Lead Manager, Data Engineering, Trust & Safety

University of California - San Francisco

<div><p><b>Job Summary:
</b></p><p>The Organizational Development Consultant &ndash; Performance Management is a senior, enterprise-level role responsible for setting and driving the strategy, governance, and effectiveness of performance management across UCSF. Reporting to the Director of Organizational Effectiveness, this role ensures that performance practices are consistent, data-driven, and fully embedded into how leaders manage, evaluate, and develop their teams.
</p><p>This position has direct accountability for strengthening the quality, integrity, and completion of performance reviews across the organization, ensuring that leaders follow through on expectations and that performance outcomes are calibrated, equitable, and aligned to enterprise standards.
</p><p>The role partners closely with HR Business Partners (HRBPs) to drive adoption and accountability within the business, while collaborating with Organizational Effectiveness and Learning &amp; Development teams to integrate performance management into broader leadership and talent strategies.
</p><p>Serves as the enterprise owner of performance management strategy and execution. Establishes frameworks, processes, and governance to ensure high-quality performance evaluations, strong completion rates, and consistent application of standards across the organization.
</p><p>Leads the design and execution of enterprise calibration processes, ensuring fairness, rigor, and alignment in performance outcomes. Owns performance data strategy, including reporting, insights, and accountability mechanisms that drive leader follow-through and continuous improvement.
</p><p>Exercises significant influence with senior leaders, HRBPs, and internal partners to reinforce a culture of accountability, differentiation, and development.
</p><p>Operating Model
</p><p>This role operates within an HRBP-led model, where HR Business Partners serve as the primary conduit to the business. The Consultant partners closely with HRBPs to align performance management strategies with business priorities and ensure consistent execution across units.
</p><p>In this model, the Consultant sets enterprise direction, standards, and expectations for performance management, while enabling HRBPs to drive adoption and accountability with leaders. The role brings structure, data, and discipline to performance practices, ensuring a consistent and aligned experience across the organization without fragmenting how the business engages with HR.
</p><p><b>Department Overview:
</b></p><p>UCSF Human Resources has a mission of attracting, developing and retaining outstanding and diverse people with a vision of being a strategic and trusted partner empowering the UCSF Health community to leverage their talents. Human Resources is committed to providing an outstanding customer experience, leading workforce strategies, creating an engaging environment focused on continuous improvement for the HR team, and demonstrating value to the organization.</p></div>

OD Consultant – Performance Management

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