Staff Product Manager, Talent Assessment Platform (AI-Driven)

About Turing

Based in Palo Alto, California, Turing is one of the world's fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilingualism, STEM and frontier knowledge; and leveraging that expertise to build real-world AI systems that solve mission-critical priorities for Fortune 500 companies and government institutions. Turing has received numerous awards, including Forbes's "One of America's Best Startup Employers," #1 on The Information's annual list of "Most Promising B2B Companies," and Fast Company's annual list of the "World's Most Innovative Companies." Turing's leadership team includes AI technologists from industry giants Meta, Google, Microsoft, Apple, Amazon, Twitter, McKinsey, Bain, Stanford, Caltech, and MIT. For more information on Turing, visit www.turing.com. For information on upcoming Turing AGI Icons events, visit go.turing.com/agi-icons.

Why this role matters

Talent is Turing’s product: our ability to match world‑class engineers to the right opportunity is the bedrock of customer value. You will lead the next generation of our AI‑first talent assessment platform—building multimodal, large‑language‑model (LLM)–powered experiences that identify skills, predict potential, and reduce bias at global scale.

Impact north star: Talent Trial Success rate > 90% (Assessed talent successfully passes trials at > 90% rate)

What you’ll do

1. Own the vision & roadmap – Establish a 3‑ to 12‑month product strategy aligned to placement quality, fairness, and speed metrics.
2. Ship 0→1 and 1→N capability – Rapidly prototype LLM‑based assessments (e.g., code agents, multimodal challenges) and scale validated solutions across 200+ skill areas.
3. Partner deeply with AI research – Translate advances in retrieval‑augmented generation (RAG), self‑critique, and RLHF into production‑grade scoring pipelines.
4. Drive data & insight loop – Instrument every assessment to capture granular telemetry; synthesize with hiring outcomes to continuously improve algorithms and UX.
5. Lead cross‑functional squads – Align engineering, design, ops, and go‑to‑market on priorities; ruthlessly manage scope to deliver quarterly impact.
6. Institutionalize responsible AI – Embed fairness, transparency, and privacy controls; meet evolving global employment regulations.
7. Evangelize internally & externally – Publish benchmarks, speak at conferences, and influence the talent‑tech ecosystem.
   
   

Success metrics (examples)

• Placement success rate, time‑to‑match, and candidate NPS.
• Assessment validity (correlation with on‑the‑job performance).
• Model bias & drift scores (gender, geography, seniority).
• Cost per assessment run.
  
  

Minimum qualifications

• 8+ years product management with 0→1 ownership; 3+ years building ML/AI or data‑intensive platforms.
• Track record shipping UX‑intensive, real‑time evaluation or proctoring systems at scale (>100 k MAU).
• Working fluency in LLM architectures, vector search, prompt engineering, and evaluation techniques.
• Analytical rigor—SQL, experimentation design, and statistical thinking.
• Exceptional storytelling and stakeholder alignment skills across C‑suite, engineering, and compliance.
• Operate with high agency in environments of ambiguity and hyper‑growth.

Preferred qualifications

• Background in psychometrics, adaptive testing, or talent/learning management systems.
• Experience with Cursor, Replit, Vercel v0.dev, or similar for rapid AI prototyping.
• Exposure to distributed, multicultural product development.
• Thought leadership in responsible AI, bias mitigation, or employment law.

First 90 Days – Outcomes

• Prototype & ship an adaptive, multimodal Video AI Interviewer MVP that spans the full assessment lifecycle:
  
  
• Create: auto‑generates diverse content (code challenges, MCQs, interview prompts)
• Capture: ingests candidate responses in code editors, text, audio, and live/async video
• Critique: leverages Turing’s agentic self‑grading pipeline with human‑in‑the‑loop review to deliver instant, bias‑controlled scoring
• Calibrate: feeds scoring & human‑review signals back into the generator and rubrics, auto‑evolving question pools, difficulty calibration, and grading logic
  
  
• Unify existing building blocks into an end‑to‑end, repeatable platform—enabling rapid iteration of agentic interviews across all phases of the hiring loop.

Advantages of joining Turing: