Senior / Staff Machine Learning Engineer, Applied AI

The role

You will improve Lila's AI models for customer-specific scientific needs. This involves training or adapting models, building evaluation loops, and integrating model behavior into product workflows.

What you will do

• Close the last-mile gap between Lila AI model capabilities and customer-specific scientific workflows.
• Build evaluation loops that measure model quality, reliability, and customer fit.
• Design experiments to improve model performance across applied customer use cases.
• Feed customer learnings, data signals, and evaluation results back into the Lila AI model improvement cycles.
• Partner with AI researchers to translate model improvements into usable capabilities.
• Work with Software to integrate model behavior into end-to-end product workflows.
• Debug model failures using traces, evaluations, customer context, and scientific feedback.
• Build reusable tooling for model adaptation, evaluation, and deployment workflows.

Required qualifications

• Strong experience building, training, adapting, or evaluating machine learning models.
• Strong software engineering skills in Python and modern ML frameworks such as PyTorch, JAX, or TensorFlow.
• Experience with distributed ML training frameworks (Megatron-LM, TorchTitan, DeepSpeed, Ray)
• Experience designing experiments, evaluation metrics, or test sets for model performance.
• Ability to debug model behavior using data, traces, logs, and qualitative feedback.
• Experience working across research and engineering teams to move ML capabilities into usable systems.
• Familiarity with large language models, multi-modal models, or agentic AI systems.
• Clear communication skills for translating customer needs into technical model improvements.

Nice to have

• Experience adapting models for customer-facing or production workflows.
• Experience with scientific, technical, or data-intensive customer use cases.
• Experience building evaluation harnesses, model monitoring, or quality dashboards.
• Familiarity with retrieval-augmented generation, tool use, or agentic workflows.
• Experience with RL post-training, such as RLHF, GRPO, or tool-augmented RL.
• Experience training MoE architectures.
• Experience working with product or customer-facing teams to translate needs into ML improvements.

Benefits

• Medical, dental, and vision coverage
• Employer-paid life and disability insurance
• Flexible time off with generous company wide holidays
• Paid parental leave
• Educational assistance program
• Commuter benefits, including bike share memberships for office based employees
• Company subsidized lunch program

About the company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. The company builds systems that can learn for themselves by combining advanced AI models with proprietary AI Science Factory™ instruments.