Natera

Lead Machine Learning & DevOps Engineer

United States

Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Healthcare, Genomics, Biotechnology, PharmaceuticalsIndustries

Lead Full-Stack Machine Learning & DevOps Engineer, AI/ML Prototyping & Production

Location: Remote Team: Therapeutics & Innovations Reports To: Director of Artificial Intelligence


About Natera

Natera is a global leader in cell-free DNA testing, revolutionizing personalized healthcare through genomics. Our Therapeutics and Innovations unit is pioneering how AI intersects with clinical applications in drug discovery, clinical development, and diagnostics.


The Opportunity

We are seeking a Senior Full-Stack ML Engineer to bridge the gap between cutting-edge AI/ML research and real-world clinical impact. This role is ideal for someone with a software engineering background who thrives on transforming early-stage ML prototypes into scalable, production-ready applications.

You’ll work alongside a team of brilliant machine learning scientists who are developing compelling tools for therapeutic and diagnostic applications. Your role is to take those V1 alpha-stage prototypes—already scientifically validated—and bring them to life as polished, secure, reliable software tools ready for internal or clinical deployment.


Key Responsibilities

  • Productionize ML prototypes: Translate alpha-stage tools (e.g. Jupyter notebooks, python packages) into scalable, secure, and maintainable production systems.
  • Full-stack engineering: Build and integrate both back-end services and front-end interfaces that are performant and user-friendly.
  • Cloud and GPU infrastructure: Design and deploy applications using GPU-accelerated cloud infrastructure (AWS); including multi-GPU inference using frameworks such as vLLM and DeepSpeed for serving large-scale foundation models.
  • AI Model Lifecycle: Oversee the full model lifecycle with versioning (MLFlow), performance monitoring (W&B), and updating strategies (A/B testing).
  • Autonomous development: Operate independently with minimal oversight, taking ownership from handoff to final deployment, and iteratively improving products based on internal and external feedback.
  • Cross-functional collaboration: Work closely with ML scientists, product leads, and clinical stakeholders to align engineering implementation with scientific and clinical goals.
  • DevOps & CI/CD: Set up and manage robust CI/CD pipelines, monitoring tools, and testing frameworks to ensure reliability and reproducibility.
  • Security & Compliance: Ensure that tools are developed with appropriate authentication, data privacy, and (where needed) HIPAA or regulatory compliance considerations.

Qualifications

  • 5+ years of experience in software engineering, ideally with a focus on ML or scientific computing.
  • Proven experience taking ML models or tools from prototype to production in a cloud environment.
  • Deep proficiency with:
    • Python, Flask/FastAPI or Django (for APIs/services)
    • JavaScript/TypeScript with React or similar (for front-end interfaces)
    • Cloud platforms like AWS, GCP, or Azure (especially GPU usage)
    • Production-scale, multi-GPU AI inference frameworks like vLLM and DeepSpeed.
    • Docker, Kubernetes, and related container/orchestration technologies
  • Experience with experiment tracking, model registry, and observability tools (e.g., MLflow, W&B) is highly desired.
  • Familiarity with model-serving tools (e.g., Triton, TorchServe, TensorFlow Serving) is a plus.
  • Experience working in a regulated or health-tech environment is a bonus, but not required.
  • Demonstrated ability to work autonomously and prioritize in a fast-paced, interdisciplinary environment.

Preferred Qualities

  • Product mindset with an eye for usability, performance, and security.
  • Comfortable reading scientific code and engaging with ML researchers.
  • Passion for health innovation, biotech, or clinical impact.
  • Experience building internal

Skills

Machine Learning
DevOps
Python
AWS
GPU
vLLM
DeepSpeed
MLFlow
W&B
Full-stack development
Back-end development
Front-end development
Cloud infrastructure
Model lifecycle management
A/B testing

Natera

Genetic testing and diagnostics solutions provider

About Natera

Natera focuses on genetic testing and diagnostics, providing advanced solutions for cancer patients, transplant patients, and individuals assessing hereditary health risks. Their main technology is cell-free DNA (cfDNA) testing, which analyzes DNA fragments in the blood to detect minimal traces of cancer and assess organ health. Natera stands out by offering specialized tests like the Signatera ctDNA test and Panorama NIPT, along with genetic counseling services. The company's goal is to improve patient care and health outcomes through accurate genetic testing.

Austin, TexasHeadquarters
2004Year Founded
$149.9MTotal Funding
IPOCompany Stage
Biotechnology, HealthcareIndustries
1,001-5,000Employees

Benefits

Flexible medical plans
Investment options
Time off
Workplace perks

Risks

Hindenburg report accuses Natera of deceptive sales practices, risking legal challenges.
New Prospera Heart features may face slow adoption by healthcare providers.
Fetal RhD NIPT demand may drop post-RhIg shortage, affecting future sales.

Differentiation

Natera's Signatera test offers personalized ctDNA analysis for cancer patients.
Prospera Heart test uses unique Donor Quantity Score for transplant rejection detection.
Panorama NIPT test is a leader in non-invasive prenatal testing with 2 million tests.

Upsides

Increased adoption of liquid biopsy techniques boosts demand for Natera's cfDNA tests.
AI integration enhances accuracy and speed of Natera's cfDNA analysis.
Growing personalized medicine trend aligns with Natera's customized genetic tests.

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