Scale AI
Overview
We’re hiring a Strategic Product Manager to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with account executives in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll own end-to-end delivery—from discovery and PRD to pilot, launch, and iteration—with deep cross-functional leadership across research, engineering, ops, and finance. What you’ll do
Ride shotgun with AEs: join customer pitches, shape solutions live, and convert needs into scoped SOWs and product plans. Translate research → product: work with client-side researchers on post-training (SFT/RLHF/RM/DPO/GRPO), evals, safety/alignment and build the primitives, data, and tooling they need. Own full lifecycle: drive discovery, write crisp PRDs, prioritize trade-offs, run experiments, ship v1s, and scale successful pilots into repeatable offerings. Lead complex customer programs: independently run high-stakes sessions with senior stakeholders; set success metrics; communicate risk and path to green. Build evaluation rigor: stand up eval suites (RLVR/benchmarks), close the loop with data quality, and publish internal learnings that raise the bar across accounts. You have
PhD in Computer Science, Machine Learning, or AI (or equivalent research experience) from a top university 5–10+ years in product/research/ENG roles working with LLMs or multimodal systems; hands-on with post-training and evaluations. Strong technical fluency: ability to read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Comfort in the field: you enjoy joining sales calls, whiteboarding solutions, and turning ambiguous asks into scoped plans. Bias to action: you ship, learn, and iterate. Nice to have
Publications in top venues (NeurIPS/ICLR/ICML), or shipped features grounded in research. Experience building agentic or evaluation systems. Prior customer-facing work with frontier labs or large AI platform teams. How you’ll work
Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: regular customer time alongside AEs and research leads; light travel as needed. Success looks like
Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The salary range is location-dependent and will be discussed with your recruiter. Benefits may include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Please note: this posting provides a general guideline for location-based salary ranges and does not constitute a guarantee of compensation. Specific salary and equity details will be shared during the interview process. About Scale AI: We develop reliable AI systems for high-stakes decisions and work with leading organizations to deploy AI at scale. We are an equal opportunity employer and value diversity in our team. If you require accommodations during the application process, please contact accommodations@scale.com. We collect and use personal data in accordance with our privacy policy and for the purposes described in our candidate communications.
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We’re hiring a Strategic Product Manager to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with account executives in high-stakes meetings, scope and pitch solutions to top AI labs, and translate research needs (post-training, evals, alignment) into clear product roadmaps and measurable outcomes. You’ll own end-to-end delivery—from discovery and PRD to pilot, launch, and iteration—with deep cross-functional leadership across research, engineering, ops, and finance. What you’ll do
Ride shotgun with AEs: join customer pitches, shape solutions live, and convert needs into scoped SOWs and product plans. Translate research → product: work with client-side researchers on post-training (SFT/RLHF/RM/DPO/GRPO), evals, safety/alignment and build the primitives, data, and tooling they need. Own full lifecycle: drive discovery, write crisp PRDs, prioritize trade-offs, run experiments, ship v1s, and scale successful pilots into repeatable offerings. Lead complex customer programs: independently run high-stakes sessions with senior stakeholders; set success metrics; communicate risk and path to green. Build evaluation rigor: stand up eval suites (RLVR/benchmarks), close the loop with data quality, and publish internal learnings that raise the bar across accounts. You have
PhD in Computer Science, Machine Learning, or AI (or equivalent research experience) from a top university 5–10+ years in product/research/ENG roles working with LLMs or multimodal systems; hands-on with post-training and evaluations. Strong technical fluency: ability to read papers, interrogate metrics, write or review complex Python/SQL for analysis, and reason about model-data trade-offs. Executive presence with world-class researchers and enterprise leaders; excellent writing and storytelling. Comfort in the field: you enjoy joining sales calls, whiteboarding solutions, and turning ambiguous asks into scoped plans. Bias to action: you ship, learn, and iterate. Nice to have
Publications in top venues (NeurIPS/ICLR/ICML), or shipped features grounded in research. Experience building agentic or evaluation systems. Prior customer-facing work with frontier labs or large AI platform teams. How you’ll work
Customer-obsessed: start from real research needs; prototype quickly; validate with data. Cross-functional by default: align research, engineering, ops, and GTM on a single plan; communicate clearly up and down. Field-forward: regular customer time alongside AEs and research leads; light travel as needed. Success looks like
Clear wins with top labs: pilots that convert to scaled programs with strong eval signals. Reusable alignment & eval building blocks that shorten time-to-value across accounts. Crisp internal docs (PRDs, experiment readouts, exec updates) that drive decisions quickly. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The salary range is location-dependent and will be discussed with your recruiter. Benefits may include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Please note: this posting provides a general guideline for location-based salary ranges and does not constitute a guarantee of compensation. Specific salary and equity details will be shared during the interview process. About Scale AI: We develop reliable AI systems for high-stakes decisions and work with leading organizations to deploy AI at scale. We are an equal opportunity employer and value diversity in our team. If you require accommodations during the application process, please contact accommodations@scale.com. We collect and use personal data in accordance with our privacy policy and for the purposes described in our candidate communications.
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