Senior Machine Learning Engineer, Agentic Science/Generative Models, AI for Biology & Translation (AIBT)
Core
Design, develop, and scale large-scale foundation models and agentic systems for therapeutic discovery, accelerating target and drug discovery.
Role type
Senior IC machine learning engineer (agentic systems & generative models)
Builds
Foundation models, LLMs, and autonomous agent systems for biology and drug discovery
Domain
Biopharmaceuticals / AI for Science
Deliverable
production ML models
Required skills
Python, PyTorch, JAX, MLOps, AgentOps, infrastructure-as-code, CI/CD, automated testing, system design
Preferred skills
Inference-time scaling optimization, distributed training on HPC, agent orchestration frameworks (LangGraph, MCP), evaluation systems for scientific correctness
Technologies
Python, PyTorch, JAX, Terraform, Helm, Kubernetes, AWS (EC2, S3, EKS, SageMaker), LangGraph, MCP
Responsibilities
Build agents that use tools and reason across multi-step scientific workflows; Build reliable interfaces between agents and biological/genomic/clinical data sources; Design evaluation harnesses checking agent output against scientific ground truth; Build, finetune, deploy, and scale foundation models and LLMs in production; Own production codebases turning research ideas into reusable software; Work with research scientists to scope open-ended problems into shippable systems
Seniority
Senior, hands-on IC
