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Machine Learning Engineer I/II, Applied AI

Lila Sciences
Location
Cambridge, MA USA; San Francisco, CA USA
Posted
12 days ago
Department
AI
What they actually want (must-haves)
  • Experience building, training, adapting, or evaluating machine learning models.
  • Strong software engineering skills in Python and modern ML frameworks such as PyTorch, JAX, or TensorFlow.
  • Experience designing experiments, evaluation metrics, or test sets for model performance.
  • Ability to debug model behavior using data, traces, logs, and qualitative feedback.
  • Experience working across research and engineering teams to move ML capabilities into usable systems.
  • Familiarity with large language models, multi-modal models, or agentic AI systems.
Nice to have
  • Experience adapting models for customer-facing or production workflows.
  • Experience with scientific, technical, or data-intensive customer use cases.
  • Experience building evaluation harnesses, model monitoring, or quality dashboards.
  • Familiarity with retrieval-augmented generation, tool use, or agentic workflows.
  • Experience with RL post-training, such as RLHF, GRPO, or tool-augmented RL.
What the job really is

In this role as a Machine Learning Engineer at Lila Sciences, you will focus on enhancing AI models tailored to customer-specific scientific needs. Your daily tasks will involve training and adapting models, building evaluation loops, and collaborating with AI researchers and software teams to integrate these models into production systems. You will also debug model behavior and design experiments to improve performance based on customer feedback.

Benefits
  • Competitive base compensation with bonus potential and 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.
  • Educational assistance program.
Things to weigh
  • No salary listed for international positions; salaries are set to local market.
  • The role requires bridging research and engineering, which may involve a steep learning curve for some candidates.
  • The focus on customer-specific workflows may require adaptability to different scientific contexts.
Job score3.6/5
Benefits4/5
Freshness5/5
Career value4/5
Role clarity5/5
Pay transparency0/5

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