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Lead the end-to-end delivery of complex LLM and Gen AI data programs for high-value clients. This involves architecting data pipelines, managing cross-functional teams, and serving as the primary technical point of contact for client research teams.
Requires 4+ years of experience in technical project operations within a startup environment and a quantitative degree in a field like Computer Science or Statistics. Candidates must possess strong coding skills in Python or SQL and a deep understanding of how LLMs are trained and evaluated.
About SuperAnnotate
SuperAnnotate helps the world’s leading AI teams build responsible, next-generation models powered by high-quality human data. We’re a fast-growing Series B startup bridging the gap between advanced AI innovation and the data that drives it. Our global network of expert specialists, scalable managed operations, precise talent matching, and full project transparency ensure unmatched data quality at scale. Trusted by innovators like Databricks and ServiceNow - and backed by NVIDIA, Dell Technologies Capital, Databricks Ventures, Cox Enterprises, and Lionel Messi’s Play Time VC - SuperAnnotate is proud to be the top-ranked AI data company on G2 for multiple consecutive years, including 2025.
We’re looking for a skilled, technical operator who can take full ownership of our most complex, high-value client engagements.
As a Strategic Projects Lead, you’ll run the end-to-end delivery of SuperAnnotate’s largest LLM and Gen AI data programs. This includes everything from scoping data collection workflows with key clients, acting as a trusted resource to researchers, diagnosing data quality issues, and reallocating resources under a tight deadline. The role touches everything: strategy, execution, client relationships, team development, and process design.
You’ll work directly with researchers, data teams, and other key stakeholders at some of the most advanced AI organizations in the world. You'll be trusted to represent SuperAnnotate at the highest level, including on technical tradeoffs, and to grow those relationships through execution and management excellence.
You don't need to be building models, but you do need to be technical enough to understand how they're trained, evaluated, and improved. That means hands-on comfort with data, code, and pipelines, and the ability to engage credibly with client engineering and research teams on LLM data challenges and evaluation approaches.
This is a full-time, hybrid position based in San Francisco.
\nWhat You'll Do4+ years of experience running complex technical projects or operations in client-facing roles, with at least some of that time in a high-growth startup environment.
A track record of owning outcomes: You’ve managed cross-functional workstreams with real accountability - and you can point to what you delivered and how.
Coding ability and analytical depth: You have solid coding skills (Python, SQL, or similar) alongside depth in machine learning, statistics, or data science.
Strong senior stakeholder communication: You’re comfortable in a room with a CTO or VP and can represent a complex project clearly, confidently, and honestly.
Sharp operational problem-solving: You diagnose issues structurally, propose solutions with clear tradeoffs, and move quickly from analysis to action.
Financial and resource fluency: You understand project margins, can build resource plans, and think about the business impact of operational decisions.
A working knowledge of the Gen AI landscape: Familiarity with how LLMs are trained and evaluated, and what drives data quality at each stage, so you can guide your team’s approach and speak knowledgeably with client research teams.
Bachelor's degree or higher in Statistics, Data Science, Machine Learning, Computer Science, Mathematics, Engineering, or a related quantitative field. CS, Math, and Engineering degrees should include meaningful ML or applied data science exposure.
Background in management consulting, investment banking, or data-intensive technical services.
MBA or equivalent advanced degree.
This role sits at the center of what SuperAnnotate does and what the AI industry needs most right now. You’ll work on problems that matter, with clients who are building the systems that will define the next decade of AI. You’ll have real ownership, real visibility, and a direct line to leadership.
Only shortlisted candidates will be contacted for an interview!
Equal Opportunity
We are an equal-opportunity employer and value diversity at our company. At SuperAnnotate diversity means to us making an effort to reflect the many experiences and identities of the outside world, and treating each other with fairness and without bias. Every day we foster an environment where people of all backgrounds not only belong, but excel to succeed as a company and grow together. We offer equal opportunity regardless of sex, sexual orientation, national origin, color, race, age, marital status, disability, gender identity, veterans and more.
SuperAnnotate bridges the gap between cutting-edge AI innovation and the high-quality human data that powers it - helping advanced AI teams build more intelligent models. With a global network of thousands of rigorously vetted experts, ethical and scalable managed operations, precise talent matching, and purpose‑built technology, SuperAnnotate delivers full project visibility and unmatched data quality. SuperAnnotate powers complex annotation, evaluation, and reinforcement learning workflows to build, evaluate and align frontier AI. Trusted by innovators like Databricks, IBM and ServiceNow - and backed by NVIDIA, Dell Technologies Capital, Databricks Ventures, Cox Enterprises, and Lionel Messi’s Play Time VC - SuperAnnotate enables the world’s top AI teams to build responsible and state‑of‑the‑art models with human data.
Offices: 100 Bush St, Suite 410, San Francisco, California 94104, US · Hanrapetutyan, 59, Yerevan, 0010, AM · Lindstedtsvägen, 24, Stockholm, 10044, SE
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