Senior AI Scientist

Key Responsibilities

• Lead the fine-tuning, distillation, and deployment of large language models (LLMs) for high-impact use cases across clinical and commercial domains
• Drive data engineering and curation processes to transform structured and unstructured data into high-quality training datasets
• Design and implement agentic AI systems using modern frameworks to enable autonomous reasoning and task execution
• Develop proof-of-concept solutions and guide their transition into scalable, production-ready systems
• Evaluate and apply advanced Generative AI methods, including SFT, PPO, DPO, and reward modeling
• Provide technical leadership and mentorship to junior scientists and engineers
• Act as a trusted technical advisor in client engagements, translating AI concepts into actionable insights
• Collaborate cross-functionally with engineering, product, and domain experts to ensure alignment with client needs and regulatory requirements
• Contribute to thought leadership, including publications and participation in leading AI/ML conferences (e.g., NeurIPS, ICML, ICLR)

Qualifications

• PhD in Computer Science, Machine Learning, AI, or related field with a strong publication record in top-tier conferences
• Proven experience in fine-tuning and optimizing large-scale language models
• Strong programming expertise in Python and experience with agentic AI frameworks (e.g., LangChain, LangGraph ecosystem)
• Hands-on experience with vector databases, knowledge graphs, and cloud platforms (preferably Azure)
• Demonstrated success delivering scalable AI/ML solutions in enterprise environments (life sciences experience preferred)
• Strong communication and stakeholder management skills, with the ability to influence senior leaders
• Proven ability to manage multiple projects, prioritize effectively, and deliver in fast-paced environments

Pay

The potential base pay range for this role, when annualized, is $108,000.00 - $270,000.00. The actual base pay offered may vary based on a number of factors including job-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part-time).

Schedule

Home-based

Location

USA (Remote)