Applied AI x Science Intern

About the Company

Crownlands is building a precision neurology discovery platform to understand root causes, subtypes, and progression of neurodegenerative and psychiatric disease. We generate large-scale human multi-omic data and build the computational systems that translate biology into clear, decision-grade outputs. We operate from first principles: assumptions are hypotheses, and everything is worth pressure-testing.

About the Role

Crownlands is seeking a summer intern to work on our multi-agent AI scientist framework used for drug discovery and evaluation. This is a hands-on internship on a fast-moving, production AI system where priorities evolve as the platform grows. You will improve core parts of our agentic pipeline—expanding agent capabilities while strengthening observability, maintenance, and evaluation. The work spans tooling, infrastructure, and internal frameworks rather than a single fixed project. This role is a good fit for someone who enjoys building, iterating, and improving real systems in an environment with high ownership and autonomy.

Responsibilities

• Agent workflow engineering: Design and implement agent-based AI workflows for drug discovery and evaluation.
• Reliability and observability: Improve stability, tracing, and debuggability of multi-agent systems (tool calling, iteration control, validation, guardrails).
• Evaluation and benchmarking: Help define benchmarks, metrics, and failure modes for agent performance; build evaluation harnesses and regression tests.
• Provider-agnostic abstractions: Build and maintain abstractions across multiple LLM backends/providers.
• Systems integration: Integrate agents with internal data systems, APIs, SQL databases, and execution environments (AWS preferred).
• Protocol design: Collaborate on prompt, schema, and protocol design for robust agent interaction.

Qualifications

• Typical background: senior student (undergraduate, master’s, or PhD) in Machine Learning, Software Engineering, Computational Biology, Bioinformatics, Data Science, or a related field.

Required Skills

• Demonstration of excellence in a competitive area, e.g., at the national level - interpret this broadly, and please bold this in your email.
• Strong Python skills and experience building ML systems beyond notebooks (pipelines, services, orchestration).
• Familiarity with LLM tooling, agent frameworks, or workflow engines (e.g., LangGraph, LangChain, or comparable custom systems).
• Experience working with structured data, APIs, SQL databases, and/or distributed systems (AWS preferred).
• Ability to reason about system behavior, edge cases, and failure modes; comfortable debugging complex flows.
• Interest in applying AI systems to real scientific or industrial problems.
• Fascination with the philosophy and underlying logic of science and discovery.

Preferred Skills

• Experience with ML/deep learning frameworks (PyTorch, JAX, TensorFlow).
• Familiarity with model architectures and training workflows (training loops, embeddings, fine-tuning, RL, or extending pretrained models).
• Experience with AI x Science architectures (scientist agents, generative syn models, bio foundation models, lab-in-the-loop/self-driving labs)

Pay range and compensation package

Compensation: Prorated $120,000 annual salary

Equal Opportunity Statement

We are committed to diversity and inclusivity.

Logistics

• Term: Summer 2026
• Duration: 12–16 weeks (flexible start date)
• Location: On-site, downtown San Francisco
• Work authorization: Must be authorized to work in the U.S.
• Support: Public transit commute support equipment provided