Applied Scientist, GenAI & ML Systems
Core
Design and deploy production-grade GenAI and ML systems, specifically focusing on LLM/SLM optimization for agentic, multi-agent architectures in cloud environments.
Role type
Senior Applied Scientist (GenAI & ML Systems)
Builds
Multi-agent systems (planner/executor, tool-using agents, supervisor patterns), production SLM models, and Advanced RAG pipelines.
Domain
Life sciences, healthcare, supply chain operations, Generative AI, Multi-agent systems
Deliverable
production ML models | product features
Required skills
LLM/SLM optimization, multi-agent system design, context engineering, fine-tuning SLMs, Advanced RAG, inference optimization, Python, cloud deployment
Preferred skills
Enterprise constraints (privacy/security), GenAI observability, scalable inference operations
Technologies
Python, AWS/Azure/GCP, Vector DBs, Containers, APIs
Responsibilities
Build and ship multi-agent systems from prototype to production; Write production-quality code for agent orchestration and tool integration; Lead context engineering strategies for multi-agent coordination; Fine-tune and deploy SLM models for production usage; Build Advanced RAG pipelines end-to-end; Implement evaluation frameworks for multi-agent systems; Collaborate with platform engineering for cloud-native solutions; Optimize for cost and latency via model routing and caching; Mentor peers through code reviews and architecture sessions.
Seniority
Senior, hands-on IC
