Lead Research Engineer Applied ML

Own high-impact AI initiatives end-to-endWork on challenging problems with real-world impact About Our Client Client is building the agentic AI layer for oncology electronic health records, enabling cancer hospitals to automate the manual review of pathology reports, clinical notes, genomic data, and other unstructured medical records. Their AI-powered platform supports use cases such as clinical trial matching, registry curation, visit preparation, and quality reporting. The platform is used by leading cancer centers including Memorial Sloan Kettering, Mount Sinai, and Yale Cancer Center, and processes millions of oncology documents each month. The company has experienced significant growth and is backed by investors such as Battery Ventures, Lightspeed, General Catalyst, Nexus Venture Partners, and Y Combinator. Job Description Lead and own major ML and LLM workstreams from problem definition through production deployment.Define technical architecture, evaluation frameworks, data requirements, and release criteria.Build NLP and LLM solutions for clinical information extraction, patient-trial matching, and real-world evidence workflows.Drive experimentation, model evaluation, error analysis, and performance improvements.Review technical designs, code quality, and experiment plans submitted by engineers.Mentor research engineers and establish engineering best practices across teams.Partner with clinical, product, MLOps, and evaluation teams to ensure scalable and reliable AI solutions.Act as the primary technical owner for workstreams and drive execution with minimal leadership oversight. The Successful Applicant We're Looking For Someone Who Has 5-10+ years of experience in Machine Learning, NLP, or LLM engineering with production deployment experience.Demonstrates a strong track record of independently owning and delivering technical workstreams.Possesses expert-level Python programming and ML engineering skills.Has deep expertise in LLMs, Transformers, RAG, embeddings, fine-tuning techniques, prompt engineering, and evaluation methodologies.Can design rigorous experiments, define meaningful metrics, and analyze model failures systematically.Has experience mentoring engineers, conducting design reviews, and influencing team performance.Is comfortable making architectural decisions and collaborating with multiple stakeholders across functions.Experience in healthcare AI, clinical NLP, oncology data, EHRs, or regulated environments is highly desirable. What's on Offer Opportunity to build AI systems that directly impact cancer research and patient outcomes.Exposure to cutting-edge challenges at the intersection of AI, healthcare, and large-scale data systems.Work with a high-caliber team across AI, engineering, and product functions.Competitive compensation package.Fast-paced, ownership-driven culture with company-sponsored workations.Complimentary office lunch.Flexible working hours focused on outcomes rather than attendance.Comprehensive health insurance coverage for employees and families, along with meal benefits. If this role aligns with your skills and interests, you're welcome to apply Contact Quote job ref: JN-062026-7050376 .