Senior AI/ML Engineer

🔥 3 hours ago

🇺🇸 United States – Remote

💵 $125k - $156.3k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Natera

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2004

🧬 Biotechnology

⚕️ Healthcare Insurance

💊 Pharmaceuticals

Biotechnology • Healthcare Insurance • Pharmaceuticals

Natera is a global leader in cell-free DNA testing technology, specializing in non-invasive genetic testing and diagnostics. The company's innovative solutions focus on areas such as prenatal screening, cancer detection, and organ transplant monitoring. By using advanced bioinformatics and DNA analysis, Natera provides healthcare professionals and patients with critical information to make more informed medical decisions.

📋 Description

• Design and implement foundational GenAI services: vector search, prompt tuning, agent orchestration, document extraction, context/memory services, model/endpoint registry, feature/embedding stores, guardrails, and evaluation pipelines • Build the underlying infrastructure for autonomous and semi-autonomous AI agents including support for agent collaboration, reasoning, and memory persistence, enabling continuous context-aware execution • Build standardized APIs/SDKs that make it easy for product teams to compose, deploy, and monitor Generative AI workloads. • Ensure platform components meet enterprise-grade requirements for scalability, latency, multi-region resilience, and cost efficiency • Stand up LLM runtimes with token/rate governance, caching, and safe tool-use • Implement RAG at scale: ingestion pipelines, chunking/embedding policies, hybrid search, relevance/risk scoring, and feedback loops • Build agent orchestration (single & multi-agent) with planning, tool routing, shared/persistent memory, and inter-agent communication • Integrate tooling and APIs that allow agents to interact with internal systems, retrieve data securely, and take action under strict controls • Collaborate with research teams to prototype and productionize multi-agent architectures for workflow automation, report generation, and data synthesis. • Implement cloud-native infrastructure for large-scale model training and serving using Kubernetes, MLflow, Terraform, and AWS-native services • Automate data and model pipelines for RAG, LLM fine-tuning, and agent orchestration • Integrate observability tools (Datadog or equivalent) for real-time performance, drift detection and safety monitoring of AI outputs • Optimize compute and storage architecture to ensure cost-effective scaling of large models and multi-agent workloads • Partner with security, data governance, SRE, and application teams to productize platform capabilities • Embed compliance-by-design (HIPAA/CLIA/CAP/FDA/GDPR): PHI/PII handling, encryption, access controls, audit trails • Implement guardrails: input/output filters, prompt hardening, allow/deny policies for tool execution, policy-as-code in CI/CD • Bias/explainability hooks and automated evaluations for RAG/LLM/agents; drift and regression detection • Establish golden paths (templates, examples, docs) and lead platform architecture reviews, code reviews, and design discussions • Partner with data scientists, AI researchers, and product engineers to deliver reliable and maintainable AI services • Mentor junior engineers in platform development, distributed systems, and agentic AI infrastructure concepts • Influence cross-functional roadmaps by partnering with Product and Engineering leadership to align delivery with business needs

🎯 Requirements

• 8+ years in software/ML engineering, with 5+ years in ML engineering at scale • Expertise in building production-grade ML/LLM systems on AWS tech stack (Python, TensorFlow/PyTorch, Spark, MLflow/Kubeflow, vector DBs) • Proven track record with GenAI/LLMs: fine-tuning, RAG, prompt orchestration, agentic systems, safety guardrails, monitoring, and cost optimization • Hands-on with RAG systems (embeddings, vector DBs, retrieval policies) and LLM runtime operations (caching, quotas, multi-model routing) • Experience building agentic AI platforms (LangChain, LlamaIndex, CrewAI, Semantic Kernel, or custom) • Deep knowledge of data-intensive systems, distributed architectures, and cloud-native development • Strong grounding in compliance-first engineering in healthcare, biotech, or diagnostics preferred • Track record building secure, compliant data/AI systems and automating policy checks. • Excellent ability to influence across teams, mentor engineers, and set technical standards.

🏖️ Benefits

• Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. • Free testing for employees and their immediate families in addition to fertility care benefits. • Pregnancy and baby bonding leave • 401k benefits • Commuter benefits • Generous employee referral program