Lila Sciences Logo

Lila Sciences

Senior Machine Learning Engineer, Physical Sciences

Reposted 12 Days Ago
In-Office
San Francisco, CA, USA
148K-240K Annually
Mid level
In-Office
San Francisco, CA, USA
148K-240K Annually
Mid level
The Machine Learning Engineer will design and implement ML pipelines and productionize models, collaborating with scientists and engineers on scalable systems.
The summary above was generated by AI

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.

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range
$148,000$240,000 USD

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

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.

Similar Jobs

16 Minutes Ago
Remote or Hybrid
45K-85K Annually
Junior
45K-85K Annually
Junior
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Handle inbound calls and warm leads, consult customers on insurance needs, recommend appropriate Property & Casualty coverages, and convert prospects into policyholders. Complete paid licensing and sales training, represent the Liberty Mutual brand, maintain strong customer relationships, and meet sales goals while working remotely on an assigned evening and weekend schedule.
Top Skills: High-Speed Wired InternetPcProperty & Casualty Insurance License
39 Minutes Ago
Easy Apply
In-Office
Easy Apply
40-45 Annually
Internship
40-45 Annually
Internship
Artificial Intelligence • Big Data • Healthtech • Machine Learning • Software • Database • Analytics
Develop Angular applications and REST APIs supporting FHIR servers, healthcare interoperability, and data platforms. Responsibilities include learning FHIR technologies, implementing reliable and scalable solutions, following UX and backend architecture practices, participating in code reviews and automated testing, and collaborating with developers and UX designers. The role requires current MIT enrollment and is based at InterSystems headquarters in Boston.
Top Skills: AngularFhirIntersystems IrisJavaObjectscriptPythonRest ApisTypescript
39 Minutes Ago
Easy Apply
In-Office
Easy Apply
40-45 Annually
Internship
40-45 Annually
Internship
Artificial Intelligence • Big Data • Healthtech • Machine Learning • Software • Database • Analytics
Build a web application interface for the Showtime integration platform. Responsibilities include gathering user needs, defining scope, designing and implementing a web interface, integrating REST endpoints, applying usability principles, testing, documentation, incorporating feedback, and demonstrating results. The role provides mentoring and experience across the software development lifecycle.
Top Skills: Ci/CdCSSGitHTMLHTTPJavaScriptJSONModern Web FrameworksRest ApisTypescript

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account