[Hiring] Technical Product Manager, Trust & Safety @Innodata

Role Description

As a Technical Product Manager for Trust & Safety, you will define and ship the data products that frontier labs use to train and evaluate models to perform personalization, computer-use (CUA), and GDPval tasks safely and in a trustworthy manner.

You will own the full lifecycle of these products:

• Translating a lab's research need into a spec
• Designing reinforcement learning (RL) environments, rubrics, and evals
• Running delivery with our expert workforce
• Measuring whether the data actually moved the model

A core part of the job is building RL environments with deliberate traps, including:

• Misalignment traps: Test for reward hacking, deception, sandbagging, oversight evasion, and power-seeking
• Cyber traps: Planted credentials, injected instructions, and poisoned tools
• Other honeypots that reveal how a model behaves when it believes no one is watching

You thrive in ambiguity, go deep on technical detail, and care about making powerful AI safe and beneficial.

Qualifications

• 5+ years of product management experience, including technical products in ML, AI data, security, or trust & safety
• Hands-on familiarity with how LLMs are trained and evaluated: SFT, RLHF/RLAIF, reward models, verifiers, and benchmark design
• Working knowledge of agentic AI: tool use, computer-use agents, multi-step planning, and the failure modes that come with them
• A strong grasp of AI safety concepts such as reward hacking, deceptive alignment, jailbreaks, and prompt injection
• Enough technical depth to read code, review an environment spec with engineers, and make sound technical tradeoffs
• Comfort with Python and sandboxed environments (Docker, VMs, browser automation) is a plus
• Experience designing metrics that capture risk, system performance, and user impact, and using them to make crisp decisions
• A track record of shipping 0-to-1 products in fast-moving, ambiguous environments
• The ability to explain complex technical ideas clearly to researchers, customers, and executives
• Creative, adversarial thinking: you enjoy imagining how a capable model might cut corners, and you don't stop at existing checklists

Requirements

• Define data products for frontier labs
• Turn lab research goals into clear product specs for safety training data, RL environments, and evaluations
• Design trap-based RL environments
• Build sandboxed environments that embed misalignment traps and cyber traps
• Build safety into agentic tasks by design
• Specify safe-behavior rubrics, verifiers, and reward signals
• Own evals and metrics
• Prioritize ruthlessly
• Partner across teams
• Track the threat landscape
• Communicate clearly

Benefits

• The expected salary range for this position is $180,000 – $220,000 USD per year, based on experience, skills, and qualifications