Senior Research Engineer

NxT Level • New York, NY

19h • Hybrid

About The Position

Our client is hiring a Research Engineer, Clinical Reasoning to help build the reasoning systems, learning methods, retrieval algorithms, post-training data pipelines, and evaluation infrastructure behind its clinical AI platform. This role blends research and engineering. The right person can run experiments, post-train models, build high-quality data pipelines, debug ML systems, and ship production-quality infrastructure that helps clinical AI improve with every iteration. This is not a pure research role and it is not a generic software engineering role. It is designed for someone with a strong spike in ML or AI research and the engineering ability to turn open-ended research ideas into working systems.

Requirements

• Strong spike in ML or AI research, especially in areas like post-training, reinforcement learning, evaluations, interpretability, model behavior, or agentic systems
• Strong software engineering ability with the ability to build reliable tools, debug systems, and ship working infrastructure
• Experience post-training models and building or curating high-quality post-training data
• Ability to design, evaluate, and improve data pipelines for model training and clinical reasoning
• Strong judgment around data quality, task realism, evaluation design, and model behavior
• Fast problem-solving and code comprehension skills, especially in unfamiliar codebases or ML pipelines
• Comfort debugging PyTorch workflows, model training issues, data pipelines, and evaluation systems
• Ability to translate research goals into concrete datasets, experiments, and measurement frameworks
• Ability to work across research and engineering, turning open-ended AI problems into usable systems
• Clear communication with research, engineering, clinical, product, and data teams

Nice To Haves

• Published research, patents, meaningful open-source contributions, or novel production ML systems
• Experience building AI systems at an early-stage or high-growth company
• Experience in healthcare, clinical AI, or another regulated or safety-critical domain
• Familiarity with clinical workflows, healthcare data, HIPAA, FHIR, EHR systems, or HL7
• Experience with human-feedback systems, RLHF, simulation, or synthetic data generation
• Experience in AI safety, bias detection, calibration, fairness, or model reliability
• Experience building evaluation harnesses for LLMs, agents, or clinical decision systems

Responsibilities

• Design and implement next-generation clinical AI reasoning systems
• Build architectures for reasoning, reflection, verification, tool use, routing, uncertainty handling, and escalation
• Create systems where specialized agents and models work together to support safe, reliable clinical decisions
• Help clinical AI systems earn greater autonomy over time through better reasoning, evaluation, and feedback loops
• Build evaluation platforms, rubrics, simulations, and experiments that measure clinical AI performance
• Identify when a benchmark score rewards the wrong behavior
• Determine whether improvements should come from reasoning, retrieval, model behavior, data, or engineering changes
• Measure whether each intervention genuinely improves safety, accuracy, usefulness, and clinical reliability
• Run post-training experiments to improve clinical AI behavior
• Apply methods such as fine-tuning, distillation, reinforcement learning, preference optimization, and prompt or system optimization
• Build training data, feedback, reward, and experimentation pipelines
• Partner with in-house researchers to translate training objectives into concrete data and evaluation specifications
• Scale training infrastructure and experimentation workflows
• Create and manage both real-world and synthetic data pipelines
• Build search, ranking, retrieval, and grounding algorithms that connect clinical reasoning to trusted medical evidence, patient context, and partner-specific content
• Improve retrieval based on downstream clinical decision quality, not just document relevance
• Build systems that help clinical AI produce grounded, evidence-backed, trustworthy answers

Benefits

• Join a frontier AI lab focused on clinical reasoning
• Work with real patient interactions and real clinical workflows
• Build systems that help clinical AI reason, learn, retrieve evidence, and improve over time
• Own problems end-to-end across research, data, training, evaluation, and deployment
• Partner with researchers, engineers, clinicians, and product teams on high-impact healthcare AI systems
• Build in a safety-critical domain where evaluation, grounding, and reliability truly matter
• Help define how clinical AI earns trust and autonomy over time

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed