Machine Learning Research Scientist - Remote

Role

The Applied AI Scientist / Machine Learning Research Scientist will design, build, evaluate, and maintain production-grade AI systems for healthcare applications. The role focuses on LLM operations, generative and predictive AI modules, agentic AI assistants, and ensuring safety, observability, and clinical alignment of deployed models.

Key Responsibilities

• Develop LLM evaluation modules and components for LLMOps, including observability, benchmark datasets, standardized metrics, and complex workflow evaluation.
• Implement AI safety strategies for adversarial detection, comprehensive model evaluation, and error analysis, incorporating human feedback loops.
• Maintain and improve data models and AI engine pipelines: monitor performance, resolve production issues, optimize for scalability, and ensure robust dataflows.
• Apply LLM observability tools for traces, latency and cost awareness, evaluation, and prompt deployment and management.
• Build data pipelines and representations (including metadata layers for clinical semantics and vector databases) to support downstream applications.
• Develop generative and predictive AI modules and data transformation components alongside agentic AI systems.
• Support agentic AI development using LangGraph or similar frameworks for internal and external AI assistant use cases.
• Collaborate with clinical domain experts and product teams to translate clinical guidelines into AI modules and ensure clinical relevance.
• Stay current with advancements in generative AI and contribute learnings to practical applications and the AI community.

Requirements

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Physics, Mathematics, Engineering, Informatics, or a related field.
• 3+ years of experience in data analytics and statistical/ML/NLP modeling, with emphasis on healthcare applications.
• Proven experience with cloud infrastructure and services for AI/ML model deployment.
• Expertise in Python programming and familiarity with AI/ML tools and frameworks.
• Familiarity with vibe coding tools (examples called out include Claude Code, Codex, Cursor, Replit).
• Demonstrated ability to develop and manage large-scale AI systems and production pipelines.
• Proficiency with cloud services and container/orchestration technologies (AWS, Azure, EKS, Docker, Kubernetes) and MLOps practices.
• Strong background in generative AI, NLP, machine learning, and data science, with emphasis on ethical and responsible AI.
• Excellent communication, leadership, project management, and collaboration skills.

Tools & Technologies (mentioned)

LangFuse, Arize Phoenix, Braintrust, LangGraph, Claude Code, Codex, Cursor, Replit, Python, AWS, Azure, EKS, Docker, Kubernetes, vector databases, LLMOps/MLOps

Benefits

• Shared premiums: medical, dental, and vision (plus access to FSA and HSA)
• 401(k) and life insurance
• Flexible vacation and holiday policies
• Flexible work hours and work-from-home options
• Paid maternity/paternity leave
• Comprehensive tech setup