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
• Partner with the Platform and Operations Lead to determine the tooling, infrastructure, and specialist talent required to deliver new offerings
• Support 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

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

Skills

Technical proficiency in machine learning, AI research, and related fields

Experience with modern ML frameworks and LLM APIs

Ability to communicate complex technical concepts clearly to both technical and non-technical audiences

Benefits

Medical, Dental, and Vision Insurance (Subsidized)

Health Savings Account

Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)

Short-Term and Long-Term Disability (Company Provided)

Life and AD&D Insurance (Company Provided)

Employee Assistance Program

Unlimited access to LinkedIn learning solutions

Matched 401(k) Retirement Savings Plan

Paid Time Off – the employee will be eligible to accrue 15-25 paid days, depending on specific level and tenure with EPAM (accrual eligibility may change over time)

Paid Holidays - nine (9) total per year

Legal Plan and Identity Theft Protection

Accident Insurance

Employee Discounts

Pet Insurance

Employee Stock Purchase Program

If otherwise eligible, participation in the discretionary annual bonus program

If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program