Principal Machine Learning Engineer, Applied AI
Core
Adapt Lila's AI models to customer-specific scientific needs by shaping frontier model capabilities into reliable workflows for evaluation and real-world use.
Role type
Principal Machine Learning Engineer (Applied AI)
Builds
Production-oriented ML systems, post-training pipelines, and evaluation loops for scientific workflows
Domain
Artificial Intelligence / Scientific Discovery
Deliverable
production ML models
Required skills
Model post-training (SFT, RLHF, DPO, PPO, GRPO), Evaluation system design, Python, PyTorch, Large Language Models, Multi-modal models, Agentic AI systems, Debugging complex model failures, Technical leadership
Preferred skills
RL post-training (RLHF, GRPO, tool-augmented RL), Model monitoring, Quality dashboards, MoE architectures, Mentoring engineers
Technologies
PyTorch, Python, SFT, RLHF, DPO, PPO, GRPO
Responsibilities
Lead post-training efforts to align model behavior with customer requirements; Build and run evaluation loops to measure model quality and reliability; Debug complex model failures using traces and scientific feedback; Partner with researchers to translate model advances into usable capabilities; Integrate model behavior into end-to-end product workflows; Mentor engineers and share reusable patterns for model adaptation.
