Founding Engineer

Proteus-Bio; San Francisco (CA); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Proteus is hiring an ML Engineer or AI Engineer to join our Biological Intelligence Platform in San Francisco and London. You will work on autonomous discovery for personalised medicine, designing models, evaluation protocols, and scalable ML systems while collaborating with cross-functional teams.

We value curiosity, ownership, and the ability to learn quickly. Biology background is welcome but not required; demonstrated projects and thinking matter more than schooling.

Qualifications

• Strong experience with PyTorch and Hugging Face Transformers, TRL, and Accelerate.
• Practical knowledge of LoRA, QLoRA and PEFT techniques.
• Familiarity with DPO/g-DPO for preference training and GRPO/PPO for online RL.
• Experience with reward models, verifiers, and outcome-based rewards.
• Experience with agent tool-use trajectories, credit assignment, and evaluation.

Responsibilities

• Develop and deploy ML/AI systems for autonomous discovery in biomedicine.
• Design evaluation protocols and run experiments with trackable results.
• Collaborate with teams to implement robust, scalable ML solutions.

Skills

PyTorch

Hugging Face

Transformers

TRL

Accelerate

LoRA

QLoRA

PEFT

DPO

PPO

online RL

Tool-use

Tools

LangGraph

RAG

Memory engineering

Tool schemas

Job description

We are hiring an ML Engineer or an AI Engineer to join Proteus in San Francisco/London.

Company Description

We are building a Biological Intelligence Platform for the autonomous discovery of personalised medicine. Our platform reasons over disease targets, designs therapeutic and diagnostic candidates, and continuously learns from experimental results.

We are looking for an:

Preferred Experience

• PyTorch and Hugging Face: Transformers, TRL, Accelerate
• LoRA, QLoRA and PEFT
• DPO / g-DPO for preference training
• GRPO / PPO for online reinforcement learning
• Reward models, rule-based verifiers and outcome-based rewards
• Tool-use trajectory collection and credit assignment
• Model evaluation, checkpointing and experiment tracking

OR

Preferred Experience

• LLM agents and tool calling
• LangGraph/stateful workflow orchestration
• RAG, memory and context engineering
• Structured outputs and typed tool schemas
• Agent evaluations, tracing and observability

AND

• Ideally knows biology, although curiosity and the ability to learn quickly matter more
• Wants to leave the world better than they found it

Biology experience is valuable, but not required. We care more about what you have built, how you think, and whether you take ownership than where you went to school.

We are backed by Founders, Inc.

If this sounds like you, tell us about something you have built that you are proud of, and why this problem interests you.