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Senior / Staff Machine Learning Engineer, Applied AI

Lila Sciences San Francisco, CA

San Francisco, CA

Today

$180k - $298k/yr Full time Senior Ai Ml Artificial Intelligence

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Job Description

Lila Sciences is hiring a Senior / Staff Machine Learning Engineer (Applied AI) to connect frontier model capabilities to customer-specific scientific workflows through post-training, evaluation, and production integration.

Responsibilities

Apply hands-on ML expertise to close the last-mile gap between model capabilities and customer scientific workflows.
Own post-training execution using methods such as SFT and RL (including DPO, PPO/GRPO) to align model behavior with customer requirements and feedback.
Run evaluation loops to measure model quality, reliability, and fit for customer use cases.
Convert customer learnings, data signals, and evaluation results into repeatable model improvement cycles.
Partner with AI researchers to translate model advances into reliable, usable capabilities.
Collaborate with Software to integrate model behavior into end-to-end product workflows.
Debug complex model failures using traces, evaluations, customer context, and scientific feedback.

Requirements

1-2 years minimum of hands-on post-training experience, including SFT and RL methods such as DPO/PPO/GRPO, plus experience designing and iterating evaluation systems.
Strong software engineering skills in Python and modern ML frameworks including PyTorch.
Proven ability to debug ambiguous, high-stakes model behavior quickly using data, traces, logs, and qualitative feedback, with judgment shaped by repeated failure-mode experience.
Deep familiarity with large language models, multi-modal models, or agentic AI systems.
Clear communication skills to translate customer needs into technical approaches and to explain complex model behavior to technical and non-technical audiences.

Technologies

Python
PyTorch
SFT
RL
DPO
PPO
GRPO

Bonus Points

Experience adapting models for customer-facing or production workflows, ideally in scientific, technical, or data-intensive domains.
Experience with RL post-training such as RLHF, GRPO, or tool-augmented RL.
Experience building evaluation harnesses, model monitoring, or quality dashboards.
Experience training MoE (Mixture of Experts) architectures.
A track record of mentoring engineers and being a go-to technical expert, rather than focusing on people management or strategy ownership.

Location and Compensation

Location: San Francisco, CA (onsite)
Salary: USD 180,000 - 298,000 per year

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