Senior AI/ML Engineer
Full-timeSenior
$126K - $157K/yr
AI Tools
CrewAILangChainLlamaIndexRAGSemantic KernelVector Databases
Tech Stack
PythonTensorFlowPyTorchSparkLangChainLlamaIndexCrewAIKubernetesTerraformAWSDatadog
Agent Workflow
Build agent orchestration (single & multi-agent) with planning, tool routing, shared/persistent memory, and inter-agent communication. Implement RAG at scale with ingestion pipelines, chunking, hybrid search. Build infrastructure for autonomous AI agents with collaboration and memory persistence.
About the Role
Natera seeks a Senior AI/ML Engineer to design, build, and deploy Generative AI and Machine Learning platforms. You will design, build, and scale enterprise-grade AI/ML systems that power internal workflows (R&D, Lab Ops, Clinical Trials, Billing, Patient/Provider engagement) and external-facing AI/ML platforms.
Key Responsibilities:
Platform Development:
- Build foundational GenAI services including vector search, prompt tuning, agent orchestration, document extraction, memory services, model registries, and evaluation pipelines
- Create infrastructure for autonomous AI agents with collaboration and persistence capabilities
- Develop standardized APIs/SDKs for product teams to deploy generative AI workloads
Generative AI Enablement:
- 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 secure tooling for agents to interact with internal systems
Infrastructure & Automation:
- Deploy cloud-native infrastructure using Kubernetes, MLflow, Terraform, and AWS services
- Implement observability tools like Datadog for monitoring AI outputs
Safety & Compliance:
- Embed compliance-by-design (HIPAA/CLIA/CAP/FDA/GDPR) protections
- Implement guardrails and bias detection for AI systems
Required Qualifications:
- 8+ years software/ML engineering; 5+ years at scale
- Production-grade ML/LLM systems on AWS (Python, TensorFlow/PyTorch, Spark)
- Proven experience with GenAI/LLMs: fine-tuning, RAG, prompt orchestration, agentic systems, safety guardrails
- Hands-on RAG experience with embeddings and vector databases
- Experience building agentic platforms (LangChain, LlamaIndex, CrewAI, Semantic Kernel)
- Strong distributed systems and cloud-native development knowledge
- Healthcare/biotech compliance engineering background preferred