Machine Learning Engineer

Responsibilities

• Design, implement, and maintain end-to-end ML pipelines including data ingestion, feature engineering, training, evaluation, deployment, and monitoring
• Productionize models and services with robust testing, observability, and documentation
• Build CI/CD workflows and automated evaluations to ensure safe, frequent releases
• Collaborate with domain scientists and platform engineers to translate research insights into performant, scalable systems
• Contribute to technical design reviews, coding standards, and mentoring of best practices

Requirements

• BS/MS/PhD in Computer Science, Engineering, or a related quantitative field
• Strong Python software engineering fundamentals including testing, packaging, and typing
• Experience with machine learning frameworks such as PyTorch or Huggingface
• Experience deploying ML services to production using cloud-based infrastructure (FastAPI/GRPC, containers, orchestration)
• Hands-on experience with model deployment in production systems (LLMs, multimodal models, databases, RAG)
• Strong debugging and profiling skills
• Clear communication and collaboration skills in cross-functional settings

Preferred Qualifications

• Exposure to scientific or engineering domains like materials, chemistry, or physics
• GPU optimization experience (CUDA, Triton, compilation, distributed training)
• Prior contributions to open-source ML or scientific software
• Experience with workflow orchestration, data provenance, or large-scale compute environments

About the Company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously.