Production ML Engineer — Physical Sciences AI

Lila Sciences, Inc.; Cambridge, San Francisco (MA, CA); Hybrid; USD 180,000 - 298,000; Full time

Job summary

Lila Sciences is hiring a Machine Learning Engineer for its Physical Sciences AI team in Cambridge and San Francisco. You will bridge research and production, turning model code into reliable, scalable services on our platform.

You’ll own end-to-end models and agentic workflows, build production AI/ML pipelines with testing and CI/CD, and collaborate with scientists and platform engineers to shape our AI/ML platform.

Qualifications

• BS/MS/PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience.
• Strong Python software engineering fundamentals (testing, packaging, typing).
• Experience deploying AI/ML services in cloud-based infrastructure (e.g., FastAPI, containers, orchestration, databases).
• Hands-on experience bringing models to production (e.g., deep learning models, LLMs, multimodal models, or RAG).
• Clear communication and collaboration in cross-functional settings.

Responsibilities

• Own models and agentic workflows end to end, from research code to a deployed, monitored service.
• Build the integration layer that lets AI agents reliably call models, tools, simulations, and data services in production.
• Profile memory and compute, catch issues early, and keep resource usage in check as workloads grow.
• Design and maintain production AI/ML pipelines with testing, observability, CI/CD, and automated evaluations.
• Partner with domain scientists, ML researchers, and platform engineers to shape architecture and best practices.

Skills

Python programming

ML frameworks

Communication & collaboration

Education

BS/MS/PhD in CS/Engineering

Tools

PyTorch

Hugging Face

FastAPI

Containers

Orchestration

Databases

Job description

Lila Sciences is hiring a Machine Learning Engineer for its Physical Sciences AI team in Cambridge and San Francisco. You will bridge research and production, turning model code into reliable, scalable services on our platform.

You’ll own end-to-end models and agentic workflows, build production AI/ML pipelines with testing and CI/CD, and collaborate with scientists and platform engineers to shape our AI/ML platform.