Machine Learning Engineer II/ Senior Machine Learning Engineer I, Physical Sciences

Your Impact at Lila

This Machine Learning Engineer for the Physical Sciences team focuses on building and operating end-to-end, scalable machine learning workflows that solve a diversity scientific use cases in materials, chemistry and physical sciences. Your work will advance research efforts on state-of-the-art algorithms to build towards scientific superintelligence across today’s greatest challenges in physical sciences.

What You'll Be Building

• Design, implement, and maintain end‑to‑end ML pipelines (data ingestion, feature engineering, training, evaluation, deployment, monitoring).
• Productionize models and services with robust testing, observability, and documentation in collaboration with cross-functional software teams and 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.

 

What You’ll Need to Succeed

• 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 with machine learning frameworks (e.g., PyTorch, Huggingface, etc.).
• Experience deploying ML services to production in cloud-based infrastructure (FastAPI/GRPC, containers, orchestration, cloud infra).
• Hands‑on experience with model deployment in production systems (LLMs, multimodal models, databases, RAG) with strong debugging and profiling skills.
• Clear communication and collaboration in cross‑functional settings.

 

Bonus Points For

• Exposure to scientific or engineering domains (materials, chemistry, physics) and related data formats/benchmarks.
• 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 Lila

Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply.

Compensation

We expect the base salary for this role to fall between $128,000 – $198,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.