Natera

Healthcare

SeniorMachineLearningScientist

$175–250k ~AI est. United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Machine Learning Scientist at Natera. Skills: Agentic AI, Foundation models, Multi-modal data, Biological reasoning. Lead technical design and deployment of multi-agent systems. Incorporate and advance Natera’s transformer-based foundation model”

What You'll Achieve.

Accelerate biomarker and therapeutic discovery; Convert multi-omic datasets into clinical insights; Provide accurate, explainable clinical rationales; Translate data into diagnostic and therapeutic insights

Industry & Context.

Healthcare
Problems you'll solve

Biological reasoning; Data-driven decision-making; Empirical model performance; Clinical validity

What They're Looking For.

Must Have

PhD or Master's degree, 8 or more years of experience in AI research or engineering, Deep experience with agentic frameworks, Retrieval-augmented generation (RAG), Validation frameworks for autonomous AI agents, Production-level development experience using PyTorch, Experience with distributed training on large GPU clusters, Ability to operate with absolute ownership, Data-driven decision-making, Technical leadership capability, Rigor in code architecture, Reproducibility, Production-grade software engineering practices, Comfort with high intellectual friction, Ability to defend scientific and engineering choices, Focus on translating machine learning outcomes into clinical utility

Nice to Have

PhD preferred, Experience with LangChain, Experience with Claude Agent SDK, Understanding of cancer genomics (WES/WTS), Understanding of mutational signatures, Understanding of structure-activity relationships, Experience with NVIDIA H100s

What You'll Do.

Lead technical design and deployment of multi-agent systems

Incorporate and advance Natera’s transformer-based foundation model

and H&E imaging modalities

Implement advanced LLM reasoning frameworks

Ensure agents provide accurate

explainable clinical rationales

Architect systems that translate multi-modal data into insights

Own technical strategy and product roadmap for agentic

Convert clinical challenges into scalable AI systems

Establish production-grade machine learning engineering standards

Ensure absolute model transparency and scientific auditability

Drive cross-functional alignment and technical consensus

Defend agentic architectures and biological reasoning frameworks

How You'll Work.

Team & Collaboration

Cross-functional alignment; Rigorous peer reviews

Communication Scope

Defend architectures; Defend reasoning frameworks

Process & Methodology

Product roadmap

Full Job Description

POSITION SUMMARY: Natera is seeking a Senior Machine Learning Scientist to join our AI team, an advanced R&D and core AI innovation team bridging the gap between molecular discovery and clinical execution. Leveraging a proprietary data moat of over 250,000 oncology patients profiled with longitudinal ctDNA, WES/WGS, digital pathology, and EMR data, you will design and deploy production-grade autonomous AI agents and multi-modal foundation models. Your mission is to architect systems capable of multi-step biological reasoning, converting complex multi-omic datasets into verifiable clinical insights that accelerate biomarker and therapeutic discovery. You will lead the next evolution of our Agentic AI platform, designing autonomous systems capable of reasoning through the complexities of cancer biology, orchestrating proprietary foundation models, and simulating virtual patient trajectories. PRIMARY RESPONSIBILITIES 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 tr

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