ML Researcher: Trustworthy AI & Evaluation

Zizy Inc.; New York (NY); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Mental health and wellness support

Generous time off policy

Paid parental leave and family-planing

Annual learning & development stipend

Job summary

Zizy Inc. is seeking an experienced machine learning researcher to shape and lead the ML research agenda for trustworthy AI.

You will pioneer evaluation methods and interventions for dangerous model capabilities, fairness, representation, and undesired model behavior. This role reports to the Trustworthy AI lead and involves mentoring, cross-functional collaboration, and building scalable tools for responsible deployment.

Qualifications

• Proven track record of ML research ideas or first author publications.
• Ability to own and pursue a research agenda with long-running projects.
• Experience developing techniques for ML model measurement and mitigation.
• Experience mentoring ML researchers and leading project teams.
• Comfortable working across research and product teams.

Responsibilities

• Research upstream interventions at training data, pre-training, and training levels.
• Prototype evaluation methods for dangerous model capabilities and existential risks, fairness and representation, and undesired model behavior.
• Collaborate with product and infra teams to build scalable tools for responsible deployment.
• Develop and mentor ML Researchers on the Deployment Planning team.
• Architect interventions that improve real-world impact.

Skills

ML research

Own research agenda

Mentorship

Cross-functional collaboration

Evaluation methods

Education

PhD or publications in ML

Tools

Deep learning frameworks

Data tooling

Job description

Zizy Inc. is seeking an experienced machine learning researcher to shape and lead the ML research agenda for trustworthy AI.

You will pioneer evaluation methods and interventions for dangerous model capabilities, fairness, representation, and undesired model behavior. This role reports to the Trustworthy AI lead and involves mentoring, cross-functional collaboration, and building scalable tools for responsible deployment.