Machine Learning Engineer, Physical Sciences AI

Lila Sciences • Cambridge, MA

12d • $180,000 - $298,000

About The Position

Lila Sciences’ Physical Science AI team uses AI to accelerate discovery in materials and chemistry, supporting the company’s mission to build Scientific Superintelligence. The Machine Learning Engineer bridges research and production by turning models and agentic workflows developed by scientists and ML researchers into reliable, scalable systems that run on the platform. Strong software engineering and experience shipping ML systems to production are central to the role; a scientific background is a plus.

Requirements

• Bachelor’s, master’s, or PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience.
• Strong Python software engineering fundamentals, including testing, packaging, and typing.
• Experience with machine learning frameworks such as PyTorch or Hugging Face.
• Experience deploying AI/ML services in cloud-based infrastructure, such as FastAPI, containers, orchestration, and databases.
• Hands-on experience bringing models to production, such as deep learning models, LLMs, multimodal models, or RAG.
• Strong debugging, profiling, and optimization skills.
• Clear communication and ability to collaborate in cross-functional settings.

Nice To Haves

• Contributions to open-source ML or scientific software.
• Experience or strong interest in building with AI agents, such as tool calling and multi-step workflows.
• Experience with workflow orchestration, data provenance, or large-scale compute environments.
• Exposure to scientific domains such as materials, chemistry, or physics, and their data formats, simulations, or benchmarks.
• Performance and memory optimization for training or inference, such as mixed precision, distributed training, GPU profiling, or efficient model serving.
• Scientific background, curiosity, and a passion for discovery.

Responsibilities

• Own models and agentic workflows end to end, from research code through deployment and monitoring.
• Build the integration layer that enables AI agents to reliably call production models, tools, simulations, and data services.
• Ensure models train correctly and models and agents run efficiently by profiling memory and compute, catching issues early, and managing resource use as workloads grow.
• Design and maintain production AI/ML pipelines covering data ingestion, training, evaluation, deployment, and monitoring.
• Build testing, observability, CI/CD, and automated evaluations into pipelines so releases are safe and results are trustworthy.
• Partner with domain scientists, ML researchers, and platform engineers.
• Help shape the architecture of the AI/ML platform, coding standards, and engineering best practices.

Benefits

• Competitive base compensation with bonus potential and generous early-stage equity.
• Medical, dental, and vision coverage for full-time U.S. employees.
• Employer-paid life and disability insurance for full-time U.S. employees.
• Flexible time off and generous company-wide holidays.
• Paid parental leave.
• Educational assistance program.
• Commuter benefits, including bike share memberships for office-based employees.
• Company-subsidized lunch program.
• Regionally tailored comprehensive benefits for full-time employees outside the U.S.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level