Senior / Staff Machine Learning Engineer, Applied AI
About the role
We are growing our Applied AI org and seeking talented Senior/Staff Machine Learning Engineers with expertise in LLM training, evaluation, and production-oriented ML systems. You’ll work on improving Lila’s AI models for 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. This is a rare chance to join an early team with the autonomy, flexibility, and compute to tackle frontier science problems.
What You'll Be Building
- 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.
What You'll Need to Succeed
- 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.
Bonus Points For
- 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.
Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
U.S. Benefits
- Medical, dental, and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with generous company wide holidays
- Paid parental leave
- An educational assistance program
- Commuter benefits, including bike share memberships for office based employees
- A company subsidized lunch program
International Benefits
Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range
$180,000 - $336,000 USD