Senior Machine Learning Scientist, Agentic AI

Natera

Senior Machine Learning Scientist leading advanced AI systems for cancer research at Natera. Designing autonomous systems for multi-step biological reasoning and clinical insights.

Posted 6/5/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $169,800 - $212,300 per yearWebsite

Tech Stack

Tools & technologies

PyTorchReact

About the role

Key responsibilities & impact

Lead the technical design and deployment of multi-agent systems capable of autonomous hypothesis generation and tool use, including genomic variant calling, LLM fine-tuning, and clinical trial matching pipelines
Incorporate and advance Natera’s transformer-based foundation model by integrating DNA, RNA, and H&E imaging modalities for multi-step biological reasoning and tool use
Implement advanced LLM reasoning frameworks, such as ReAct and Chain-of-Thought, alongside reinforcement fine-tuning (RFT) to ensure agents provide accurate, explainable clinical rationales
Architect systems that autonomously translate complex, multi-modal data into diagnostic and therapeutic insights with human-verifiable reasoning and tracing
Own the technical strategy and product roadmap for agentic workflows across the Biopharma Solutions and Therapeutics Discovery division, converting complex clinical challenges into scalable AI systems
Establish production-grade machine learning engineering standards and reproducible architectures across the AI team to ensure absolute model transparency and scientific auditability
Drive cross-functional alignment and technical consensus by defending agentic architectures and biological reasoning frameworks in rigorous peer reviews

Requirements

What you’ll need

PhD or Master's degree in Computer Science, Bioinformatics, Statistics, or a related quantitative field
8 or more years of experience in AI research or engineering, with a proven track record of moving multi-agent orchestration architectures or large-scale language model workflows from prototype to production
Deep experience with agentic frameworks, such as LangChain or Claude Agent SDK, retrieval-augmented generation (RAG), and validation frameworks for autonomous AI agents
Strong understanding of cancer genomics (WES/WTS), mutational signatures, and structure-activity relationships
Advanced production-level development experience using PyTorch and experience with distributed training on large GPU clusters, including NVIDIA H100s.

Benefits

Comp & perks

Annual performance incentive bonus
Long-term equity awards
Comprehensive health benefits (medical, dental, vision)
401(k) with company match
Generous paid time off and company holidays
Additional wellness and work-life benefits

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

multi-agent systemshypothesis generationgenomic variant callingLLM fine-tuningclinical trial matchingreinforcement fine-tuningmachine learning engineeringPyTorchdistributed traininglarge-scale language model workflows

Soft Skills

technical strategycross-functional alignmenttechnical consensuspeer reviews

Certifications

PhDMaster's degree