Principal Machine Learning Engineer, Applied AI
Hybrid (Cambridge, MA and San Francisco, CA)$252k - $336kfull-timePosted 1w ago
About the role
Senior IC role focused on model post-training, evaluation, and production-oriented ML systems to adapt Lila models to customer scientific workflows and turn frontier capabilities into reliable end-to-end products.
Responsibilities
- 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 with customer-specific requirements and feedback.
- Build and run evaluation loops that measure model quality, reliability, and customer fit, using patterns you've refined across many prior projects.
- Turn customer learnings, data signals, and evaluation results into concrete model improvement cycles.
- Partner with AI researchers to translate model advances into reliable, usable capabilities.
- Work with Software to integrate model behavior into end-to-end product workflows.
- Debug complex model failures using traces, evaluations, customer context, and scientific feedback.
- Mentor engineers and share reusable patterns for model adaptation, evaluation, and deployment, drawing on lessons learned across a long track record of shipping ML systems.
Qualifications
- 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.
- Demonstrated ability to debug ambiguous, high-stakes model behavior quickly, using data, traces, logs, and qualitative feedback.
- 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.
Skills
Required:Post-training model fine-tuning and evaluationPythonPyTorchDebugging complex model behaviorCommunication
Benefits
- Full-time U.S. employees receive medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous holidays; paid parental leave; educational assistance; commuter benefits including bike share; company lunch program.
Last updated Oct 14, 2026. Interested? Apply on the company site.
About Lila Sciences
Pioneering Scientific Superintelligence
Pioneering Scientific Superintelligence to solve humankind’s greatest challenges.
Scientific SuperintelligenceAIAutonomous LabsLife SciencesChemical SciencesMaterials Sciences
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