Technical Product Manager, Trust & Safety

Innodata Knowledge Services, Inc.; Ridgefield Park (NJ); Remote; USD 180,000 - 220,000; Full time

Job summary

Innodata Knowledge Services, Inc. is seeking a Technical Product Manager for Trust & Safety to define data products used to train and evaluate AI models for safety in personalization and computer-use tasks.

You will translate lab research into specs, design RL environments, rubrics, and evaluations, and oversee delivery with our expert teams. You’ll build safety-focused metrics, construct trap-based RL environments, and collaborate with ML researchers, platform engineers, policy experts, and

Qualifications

• 5+ years of product management experience in ML/AI data, security, or trust & safety.
• Hands-on familiarity with how LLMs are trained and evaluated (SFT, RLHF/RLAIF, reward models).
• Ability to design metrics that capture risk and system performance for AI safety.

Responsibilities

• Define data products for frontier labs and safety training.
• Design trap-based RL environments with misalignment traps and cyber traps.
• Specify safe-behavior rubrics, verifiers, and reward signals for reliable models.
• Own evals and metrics for safety and trustworthiness across products.
• Collaborate with lab researchers, ML engineers, red-teamers, policy experts, and delivery leads.

Skills

Product management

ML/AI data

Security concepts

Trust & Safety

Requirements gathering

Job description

Technical Product Manager, Trust & Safety

Remote - United States

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.

Scope of the Role:

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.

What You’ll Own:

• 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 (reward hacking, specification gaming, deception, sandbagging, oversight subversion) and cyber traps (prompt injection, credential exfiltration, tool poisoning, unsafe file and network actions).
• Build safety into agentic tasks by design. Specify safe-behavior rubrics, verifiers, and reward signals so that models learn to complete real work while refusing, escalating, or asking for confirmation at the right moments.
• Own evals and metrics. Define what "safe and trustworthy" means for each product in measurable terms, including attack success rate, over-refusal, trap trigger rate, and task completion under adversarial pressure. Track blind spots and drive iteration.
• Prioritize ruthlessly. Frame problems crisply, lay out options with their business and technical tradeoffs, and separate MVP from ideal state.
• Partner across teams. Work with lab researchers, our ML and platform engineers, red-teamers, policy experts, and delivery leads running large expert annotator pools.
• Track the threat landscape. Stay current on agentic risks, alignment research, and new attack techniques, and turn them into roadmap items before customers ask.
• Communicate clearly. Write specs, customer briefs, and safety findings that land with researchers and executives alike.

These examples show the kind of work this role owns:

• cyber-trap environment suite : sandboxed environments seeded with injected instructions, exposed secrets, and destructive shortcuts, scored on whether the agent finishes the task without taking the bait.
• Tasks with integrity traps : realistic work where the easiest path to a high score requires fabricating data, skipping a required step, or gaming the grader.
• A misalignment eval harness : environments that check whether a model behaves differently when it believes it is being tested versus deployed, or when given chances to expand its own permissions.
• A trap library and quality framework that lets our delivery teams produce new environments quickly while keeping verifiers reliable and traps hard to detect.

You’ll Thrive in This Role If You Have:

• 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.
• 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.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey.Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file.

As set forth in Innodata Inc.'s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.