Machine Learning Engineer, Physical Sciences AI
Company websitelila.ai (Lila Sciences, opens in new tab)
Base salary $180K to $298K
Employer-published annual base salary, USD. Advertised base range in United States
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationUnited States
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (2 h ago) · observed since
About this job
Your Impact at LILA
Lila's Physical Science AI team uses AI to accelerate discovery in materials and chemistry. It’s a core part of Lila's mission to build Scientific Superintelligence and solve some of humanity’s most important challenges. As a Machine Learning Engineer, you’ll be the bridge between research and production. You’ll take models and agentic workflows built by our scientists and ML researchers and turn them into reliable, scalable systems that run on our platform every day. What matters most is strong software engineering and real experience shipping ML systems to production. A scientific background is a plus, but curiosity and a passion for discovery are what will make you thrive here.
What You'll Be Building
- 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.
- Make sure models train correctly and that models and agents run efficiently, including profiling memory and compute, catching issues early, and keeping resource usage in check as workloads grow.
- Design and maintain production AI/ML pipelines (data ingestion, training, evaluation, deployment, monitoring), with testing, observability, CI/CD, and automated evaluations built in so releases are safe and results are trustworthy.
- Partner with domain scientists, ML researchers, and platform engineers, and help shape the architecture of our AI/ML platform, coding standards, and engineering 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) and experience with machine learning frameworks (e.g., PyTorch, Hugging Face).
- 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), with strong debugging, profiling, and optimization skills.
- Clear communication and collaboration in cross-functional settings.
Bonus Points For
- Contributions to open-source ML or scientific software.
- Experience or strong interest in building with AI agents (e.g., tool calling, multi-step workflows).
- Experience with workflow orchestration, data provenance, or large-scale compute environments.
- Exposure to scientific domains (materials, chemistry, or physics) and their data formats, simulations, or benchmarks.
- Performance and memory optimization for training or inference (e.g., mixed precision, distributed training, GPU profiling, efficient model serving).
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
$180,000—$298,000 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.
Source: Lila Sciences on Greenhouse · View original posting (opens in new tab)
Pay in context
This role's base floor ($180,000) is above 40% of the 1,463 Data & ML roles in California listed on this site; 55 others list the same floor. Their median floor is $190,000; the middle half runs from $160,000 to $229,900.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 5, 2026.
This listingMachine Learning Engineer, Physical Sciences AI$180K to $298K
Senior II/ Staff Software Engineer, Platform Operations$180K to $288K
Senior Product Designer II / Staff Product Designer$180K to $256K
Senior / Staff Machine Learning Engineer, Applied AI$180K to $298K
Senior Software Engineer, Operations Research$180K to $256K
Manager / Senior Technical Program Manager$180K to $256K
Senior / Staff Machine Learning Engineer, Applied AI$180K to $298K
Chart as a table
| Role | Published base |
|---|---|
| Machine Learning Engineer, Physical Sciences AI (this listing) | $180K - $298K |
| Senior II/ Staff Software Engineer, Platform Operations | $180K - $288K |
| Senior Product Designer II / Staff Product Designer | $180K - $256K |
| Senior / Staff Machine Learning Engineer, Applied AI | $180K - $298K |
| Senior Software Engineer, Operations Research | $180K - $256K |
| Manager / Senior Technical Program Manager | $180K - $256K |
| Senior / Staff Machine Learning Engineer, Applied AI | $180K - $298K |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-02-03
Where this pay comes from
Location as the employer wrote it: Cambridge, MA USA; San Francisco, CA USA
USD 180,000 – 298,000 · interval unstated · pay_input_range · Expected Base Salary Range · base-labelled (R1: Base Salary)
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
