Senior / Staff Machine Learning Engineer, Applied AI
Lila Sciences3 months ago
Cambridge, MA, USA or San Francisco, CA, USASenior / Staff+
H1B sponsor
Responsibilities
- 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 into AI model improvement cycles.
- Partner with AI researchers to translate model improvements into usable capabilities.
- Work with software teams 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.
Requirements
- Strong experience building, training, adapting, or evaluating machine learning models.
- Strong software engineering skills in Python and modern machine learning frameworks such as PyTorch, JAX, or TensorFlow.
- Experience with distributed machine learning training frameworks including Megatron-LM, TorchTitan, DeepSpeed, or 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 collaborating across research and engineering teams to move machine learning capabilities into usable systems.
- Familiarity with large language models, multimodal models, or agentic AI systems.
- Clear communication skills for translating customer needs into technical model improvements.
- Preferred experience adapting models for customer-facing or production workflows; working with scientific, technical, or data-intensive use cases; building evaluation harnesses, model monitoring, or quality dashboards; using retrieval-augmented generation, tool use, or agentic workflows; reinforcement learning post-training such as RLHF, GRPO, or tool-augmented RL; training mixture-of-experts architectures; and collaborating with product or customer-facing teams.
Categories
About Lila Sciences
Lila Sciences builds an AI-driven research platform and autonomous lab systems for life science, chemistry, and materials R&D teams. Its products combine large AI models with robotic instruments to plan, run, and analyze experiments, integrating into customer-specific scientific workflows. The privately held company serves pharma, materials, and energy organizations and is venture-backed, including a Series A financing in 2025.