Scale AI
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AI Architect
role at
Scale AI
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About The Role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams 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 drive end‑to‑end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting‑edge research into deployable, high‑impact solutions.
What You’ll Do
Translate research → product: work with client side researchers on post‑training, evals, safety/alignment and build the primitives, data, and tooling they need.
Partner deeply with core customers and frontier labs: work hands‑on with leading AI teams and frontier research labs to tackle hard, open‑ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post‑training, evaluation, and safety work into well‑defined statements of work and execution plans.
Translate research into production impact: collaborate with customer‑side researchers on post‑training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice.
Own the end‑to‑end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade‑offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings.
Lead complex, high‑stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes.
Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production‑grade results for demanding customers.
Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts.
You have
Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high‑stakes, customer‑facing environments.
Hands‑on experience with model improvement workflows: demonstrated experience with post‑training techniques, evaluation design, benchmarking, and model quality iteration.
Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models.
Strong technical fluency: you can 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.
Bias to action: you ship, learn, and iterate.
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: expect regular customer time and research leads; light travel as needed.
What 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 range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job‑related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. For pay transparency purposes, the base salary range for this full‑time position in the locations of San Francisco, New York, Seattle is: $190,000—$230,000 USD Our policy requires a 90‑day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Design, Art/Creative, and Information Technology
Industries Software Development
Referrals increase your chances of interviewing at Scale AI by 2x
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AI Architect
role at
Scale AI
Get AI‑powered advice on this job and more exclusive features.
About The Role We’re hiring an AI Architect to sit at the intersection of frontier AI research, product, and go-to-market. You’ll partner closely with ML teams 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 drive end‑to‑end delivery—partnering with AI research teams and core customers to scope, pilot, and iterate on frontier model improvements—while coordinating with engineering, ops, and finance to translate cutting‑edge research into deployable, high‑impact solutions.
What You’ll Do
Translate research → product: work with client side researchers on post‑training, evals, safety/alignment and build the primitives, data, and tooling they need.
Partner deeply with core customers and frontier labs: work hands‑on with leading AI teams and frontier research labs to tackle hard, open‑ended technical problems related to frontier model improvement, performance, and deployment. Shape and propose model improvement work: translate customer and research objectives into clear, technically rigorous proposals—scoping post‑training, evaluation, and safety work into well‑defined statements of work and execution plans.
Translate research into production impact: collaborate with customer‑side researchers on post‑training, evaluations, and alignment, and help design the data, primitives, and tooling required to improve frontier models in practice.
Own the end‑to‑end lifecycle: lead discovery, write crisp PRDs and technical specs, prioritize trade‑offs, run experiments, ship initial solutions, and scale successful pilots into durable, repeatable offerings.
Lead complex, high‑stakes engagements: independently run technical working sessions with senior customer stakeholders; define success metrics; surface risks early; and drive programs to measurable outcomes.
Partner across Scale: collaborate closely with research (agents, browser/SWE agents), platform, operations, security, and finance to deliver reliable, production‑grade results for demanding customers.
Build evaluation rigor at the frontier: design and stand up robust evaluation frameworks (e.g., RLVR, benchmarks), close the loop with data quality and feedback, and share learnings that elevate technical execution across accounts.
You have
Deep technical background in applied AI/ML: 5–10+ years in research, engineering, solutions engineering, or technical product roles working on LLMs or multimodal systems, ideally in high‑stakes, customer‑facing environments.
Hands‑on experience with model improvement workflows: demonstrated experience with post‑training techniques, evaluation design, benchmarking, and model quality iteration.
Ability to work on hard, ambiguous technical problems: proven track record of partnering directly with advanced customers or research teams to scope, reason through, and execute on deep technical challenges involving frontier models.
Strong technical fluency: you can 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.
Bias to action: you ship, learn, and iterate.
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: expect regular customer time and research leads; light travel as needed.
What 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 range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job‑related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. For pay transparency purposes, the base salary range for this full‑time position in the locations of San Francisco, New York, Seattle is: $190,000—$230,000 USD Our policy requires a 90‑day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Design, Art/Creative, and Information Technology
Industries Software Development
Referrals increase your chances of interviewing at Scale AI by 2x
#J-18808-Ljbffr