LILA has created the world's first Operating System for Science powered by Scientific Superintelligence™. Backed by General Catalyst.
About the role
We are growing our Applied AI org and seeking a Principal Machine Learning Engineer, Applied AI with deep expertise in model post-training, evaluation, and production-oriented ML systems. You’ll shape how Lila’s AI models are adapted to customer-specific scientific needs, with a focus on turning frontier model capabilities into reliable workflows that can be evaluated, iterated and used in real customer contexts. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Minimum 2-3 years of hands-on post-training experience (SFT, RL methods such as DPO/PPO/GRPO) and evaluation system design, gained from having solved these problems many times before
- Strong software engineering skills in Python and modern ML frameworks like PyTorch
- A demonstrated ability to debug ambiguous, high-stakes model behavior quickly, using data, traces, logs, and qualitative feedback - the kind of judgment that only comes from having seen many failure modes before
- Experience leading technical work across research and engineering teams
- Deep familiarity with large language models, multi-modal models, or agentic AI systems
- Clear communication skills for translating customer needs into technical approaches, and for explaining complex model behavior to both technical and non-technical audiences
More about this role
We are growing our Applied AI org and seeking a Principal Machine Learning Engineer, Applied AI with deep expertise in model post-training, evaluation, and production-oriented ML systems. You’ll shape how Lila’s AI models are adapted to customer-specific scientific needs, with a focus on turning frontier model capabilities into reliable workflows that can be evaluated, iterated and used in real customer contexts.
Applied AI sits at the intersection of AI Research, model engineering, and product deployment. The team partners closely with AI Researchers and Software teams to adapt Lila models to customer workflows, improve model quality through post training and driving how harness engineering shapes model behavior inside the product.
This is a high-impact senior IC role for someone who brings deep, hands-on expertise in model post-training, evaluation, and production ML systems, built over many years of solving this exact class of problem.
- Apply deep, hands-on expertise to close the last-mile gap between Lila's model capabilities and customer-specific scientific workflows.
- Lead post-training efforts using approaches such as SFT and RL (DPO, PPO/GRPO) to align model behavior...
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