Senior Director, Frontier AI Research, Bay Area, NY

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
• Provide technical oversight during early and strategically important engagements, reviewing outputs and model behavior to confirm the program is producing the intended results

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
• 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

Qualifications

None specified.

Skills

None specified.

Benefits

See detailed benefits section in job posting.

Pay

$250,000-$325,000 USD.

Schedule

Remote Position.