AI Engineer, Agents for Biochemistry
Core
Build and evaluate multi-agent systems for scientific reasoning, integrating retrieval, knowledge graphs, and inference methods to process biological and chemical data.
Role type
Senior IC AI Engineer (Multi-Agent Systems for Biochemistry)
Builds
Automated agent harnesses, retrieval layers, extraction pipelines, and evaluation benchmarks for scientific tasks.
Domain
Biochemistry, Cheminformatics, Scientific Data Infrastructure
Deliverable
production ML models
Required skills
Multi-step LLM agent development, LLM evaluation & benchmarking, Python (production backend), Schema modeling (relational/graph DBs), Advanced retrieval systems, Primary literature reading (biology/chemistry)
Preferred skills
Multi-agent orchestration (MCP), Probabilistic programming/Bayesian inference, Non-monotonic logic, Information extraction (table/layout parsing), RL/LLM finetuning, Cheminformatics (RDKit, SMILES, OCR), Chemical biology/Proteomics, Scientific data infrastructure (ELN, LIMS, FAIR)
Technologies
Python, Knowledge Graphs, Relational Databases, Graph Databases, RDKit, SMILES, ELN, LIMS
Responsibilities
Design memory strategies and tool interfaces for agents; Debug agent failures at trajectory level; Build retrieval layers with query planning and reranking; Implement inference for incomplete/conflicting evidence; Construct benchmarks for scientific reasoning; Own automated evaluation harnesses; Integrate third-party scientific databases.
Seniority
Senior, hands-on IC
