Machine Learning Engineer I/II, Applied AI
Lila Sciences · Cambridge, MA USA; San Francisco, CA USA
Posted 8 days ago
or apply directly on Lila Sciences's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 8 days Lila Sciences's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- No 0% of Lila Sciences's roles list one
- Ghost-job risk at Lila Sciences
- high 89 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
- 2026-09-17
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
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
- 4/5
- freshness
- 5/5
- career value
- 4/5
- role clarity
- 5/5
- 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
- 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 you get
- 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.
Worth weighing
- 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.
Summarised from Lila Sciences's posting. Read the full original.
Listed by Lila Sciences on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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