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Principal AI/ML Platform Engineer

United States

Full-time

Remote

Lead/Staff

$174K/yr - $218K/yr

12+ years exp

Natera is a company focused on innovative healthcare solutions, and they are seeking a Principal AI/ML Platform Engineer. This role involves leading the design and delivery of advanced AI and ML platforms that enhance patient outcomes and clinical innovation.

Computer Software

Responsibilities

Define the technical vision and architecture for Natera's ML and GenAI platforms, ensuring scalability, reliability, and compliance across diverse use cases

Build, operate, and evolve core AI platform components for standardized data access, LLM model registries for versioning and lifecycle tracking, evaluation pipelines for model validation and monitoring, vector databases, RAG frameworks, and agent frameworks for GenAI applications, prompt orchestration and guardrails for safe and compliant LLM deployments

Design, build, and operate end-to-end ML/DL/FM infrastructure (feature engineering, distributed training, evaluation, deployment, monitoring) that are modular, reproducible, and auditable

Design, build, and operate reusable GenAI services such as unstructured data extraction, classification, summarization, generation, retrieval from knowledge bases, prompt optimization etc

Implement production-grade Gen AI and ML services and API's that power critical workflows, from genomics analytics to clinical trial optimization to patient-facing solutions

Lead the deployment and scaling of large models (custom trained LLMs, multimodal, deep learning) using modern MLOps practices (Kubernetes, MLflow, AWS-native services)

Deliver retrieval-augmented generation (RAG), agentic runtime, agent orchestration frameworks, and domain-specific copilots in compliance-ready environments

Optimize inference latency, throughput, and cost-efficiency through infrastructure design and algorithmic improvements

Build online and offline evaluation frameworks to ensure performance and real world utility

Embed governance and monitoring guardrails into AI and ML pipelines, including bias testing, safety, security, hallucination, explainability, PHI/PII redaction, audit trails

Partner with the Head of Data & AI Governance to ensure adherence to HIPAA, CLIA, CAP, FDA, GxP, GDPR, and emerging AI regulations

Establish automated checks and controls in the CI/CD and SDLC processes to maintain compliance-by-design

Act as the principal technical authority in AI/ML engineering — set coding standards, review designs, and ensure best practices in reproducibility, monitoring, and observability

Mentor and guide other engineers and data scientists, providing thought leadership on system design, optimization, and responsible AI

Influence cross-functional roadmaps by partnering with Product, Data Governance, and Engineering leadership to align delivery with business needs

Evaluate and integrate emerging AI/ML technologies (foundation models, multimodal AI, biomedical reasoning agents, federated learning)

Lead build vs. buy assessments for AI/ML tooling and platforms; integrate open-source or vendor solutions where appropriate

Prototype and productionize new approaches (e.g., foundation model fine-tuning, GenAI copilots for lab workflows, advanced monitoring frameworks)

Represent Natera's AI/ML technical capabilities externally at conferences, publications, and industry forums

Qualification

AI/ML engineeringAWS tech stackGenAI/LLM systemsProduction-grade systemsDistributed architecturesAI governance frameworksCompliance-first engineeringInfluence across teamsTechnical standardsMentorship

Required

12+ years in software/data/ML engineering, with 8+ years in AI/ML engineering at scale

Expertise in building production-grade ML/LLM systems on AWS tech stack (E.g. Python, LangChain/Llamaindex, CrewAI, Vector databases, Agent runtimes, TensorFlow/PyTorch, Spark, MLflow)

Proven track record with GenAI/LLMs: fine-tuning, RAG, prompt orchestration, safety guardrails, monitoring, and cost optimization

Deep knowledge of AI/ML intensive systems, distributed architectures, and cloud-native development

Familiarity with AI governance frameworks, LLM safety, drift detection, bias detection, hallucination, explainability, and compliance (e.g., HIPAA, CLIA, FDA)

Strong grounding in compliance-first engineering in healthcare, biotech, or diagnostics preferred

Excellent ability to influence across teams, mentor engineers, and set technical standards