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Lila Sciences

Senior Machine Learning Engineer, Physical Sciences

Lila Sciences · Cambridge, MA USA; San Francisco, CA USA

Posted about 3 months ago

or apply directly on Lila Sciences's site. We never take the application ourselves.

Is this posting real?

This role has been open
80 days
Lila Sciences's roles stay open a median of 80 days
Reposted
No
Salary listed
No
0% of Lila Sciences's roles list one
Ghost-job risk at Lila Sciences
high
116 stale, 2 reposted of 118 open
Hiring momentum
155 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-10-22

Measured from postings appearing on and disappearing from Lila Sciences's own greenhouse board since 2026-08-03. Full hiring picture for Lila Sciences.

About this role

As a Machine Learning Engineer on Lila's Physical Science AI team, you will transform AI models and workflows from research into reliable, scalable systems for production. Your responsibilities will include building integration layers for AI agents, designing production AI/ML pipelines, and collaborating with scientists and engineers to shape the architecture of the AI/ML platform. Strong software engineering skills and experience in deploying ML systems are crucial for success in this role.

Our read on this posting2.8out of 5
benefits
5/5
freshness
1/5
career value
4/5
role clarity
4/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Lila Sciences as an employer.

What you need

  • 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, 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)
  • Strong debugging, profiling, and optimization skills

Nice to have

  • 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)

What you get

  • Competitive base compensation with bonus potential
  • Generous early-stage equity
  • 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

Worth weighing

  • No specific mention of the tech stack beyond Python and ML frameworks
  • The role requires strong collaboration with cross-functional teams, which may require adaptability
  • The company is in an early-stage environment, which may involve uncertainty and rapid changes

Summarised from Lila Sciences's posting. Read the full original.

Listed by Lila Sciences on their greenhouse job board, last confirmed open on 2026-10-22. PitchMeAI is not the employer.

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