Technical Product Manager, Trust & Safety

• 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.

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

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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: from translating a lab's research need into a spec, to designing reinforcement learning (RL) environments, rubrics, and evals, to running delivery with our expert workforce and measuring whether the data actually moved the model.

A core part of the job is building RL environments with deliberate traps. That includes misalignment traps that test for reward hacking, deception, sandbagging, oversight evasion, and power-seeking; cyber traps such as planted credentials, injected instructions, and poisoned tools; and 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.

Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.