Senior Director, Frontier AI Research, Bay Area, NY

EPAMs new Frontier AI business unit partners directly with leading AI labs and advanced AI organizations translating their research and post-training objectives into technically rigorous deliverable programs across evaluations RL environments and training data.

The Senior Director Frontier AI Research is EPAMs first dedicated Frontier AI research hire operating across a broad set of capabilities rather than a single research domain. The role sits at the intersection of research solution architecture and technical sales remaining technically engaged through early pilots while delivery leadership owns day-to-day execution.

The right person is a genuine technical peer to sophisticated AI researchers: someone who can translate ambiguous research goals into concrete specifications that delivery teams can execute at quality and scale.

Req.#

Responsibilities

• Engage directly with researchers engineers and technical leaders at frontier AI labs to understand model training post-training and evaluation objectives
• Translate ambiguous research goals into explicit target capabilities failure modes and success criteria advising customers and internal teams on the right technical approach
• Design rigorous evaluation approaches including task taxonomies benchmarks rubrics and graders and analyze model outputs to identify failure modes and improvement opportunities
• Help architect RL environments reward functions and verifiers that provide reliable training and evaluation signals while mitigating reward hacking and weak verification
• Design technically rigorous training data programs (SFT preference data RLHF) defining task distributions annotation criteria and quality standards
• Translate recurring customer research needs into repeatable EPAM Frontier AI offerings methodologies and technical assets
• Partner with the Platform and Operations Lead to determine the tooling infrastructure and specialist talent required to deliver new offerings
• Serve as the primary research and technical SME supporting Frontier AI Sellers in strategic customer pursuits from discovery through solution design
• Translate customer requirements into technically compelling solution designs proposals and pilot plans that establish credibility with sophisticated AI research organizations
• Convert research requirements into clear specifications including scope rubrics and quality thresholds that delivery teams can execute without losing the research intent
• Provide technical oversight during early and strategically important engagements reviewing outputs and model behavior to confirm the program is producing the intended results
• Maintain strong familiarity with developments in frontier model training post-training RL agentic systems and evaluation and apply that knowledge to EPAMs offerings
• Build relationships across the Frontier AI research ecosystem and contribute to technically credible customer facing content and thought leadership

Requirements

• Significant experience in machine learning AI research or research engineering with demonstrated work on modern deep learning and large language models
• Strong understanding of the model training and post-training lifecycle including SFT RLHF reward modeling and evaluation
• Demonstrated depth in one or more Frontier AI focus areas (evaluations RL environments agentic systems reward or verifier design coding agents) with the breadth to operate across adjacent areas
• Experience translating ambiguous research objectives into structured experiments datasets evaluations or environments
• Hands-on technical capability including strong Python skills and experience with modern ML frameworks LLM APIs and evaluation tooling
• Demonstrated ability to communicate complex technical concepts clearly to both technical and cross-functional audiences
• Advanced degree in Computer Science Machine Learning AI Statistics or a related field or equivalent demonstrated research experience

Nice to have

• Peer-reviewed AI/ML research or a strong record of technically substantive applied research
• Prior experience building solutions or conducting research for frontier AI labs or leading foundation model companies
• Direct experience with RLHF RLAIF preference optimization or synthetic data generation and curation
• Comfortable operating as a genuine technical peer to sophisticated researchers with the commercial awareness to translate research credibility into customer trust
• Entrepreneurial mindset comfortable building a new capability and creating structure where established process does not yet exist

Required Experience:

Exec