Applied AI ML Engineer - Train, Evaluate & Deploy

Lila Sciences; Cambridge (MA); On-site; USD 116,000 - 170,000; Full time

Benefits offered by this job

Equity

Bonus potential

Comprehensive benefits

Job summary

Lila Sciences is seeking Machine Learning Engineers to turn frontier model capabilities into reliable customer workflows. You will train, adapt, and evaluate models, build evaluation loops, and collaborate with AI researchers and software engineers to deploy end-to-end solutions.

The role bridges research and engineering with autonomy, offering the chance to shape production‑quality systems in a fast‑moving environment.

Qualifications

• Experience building, training, adapting, or evaluating machine learning models.
• Strong software engineering skills in Python and ML frameworks (PyTorch/JAX/TF).
• Experience designing experiments, evaluation metrics, or test sets for model performance.

Responsibilities

• Close the last-mile gap between Lila AI model capabilities and customer-specific scientific workflows.
• Post-train models using approaches like SFT and RL (DPO, PPO/GRPO) to align behavior with requirements.
• Build evaluation loops that measure model quality, reliability, and customer fit.
• Design experiments to improve model performance across use cases.
• Feed customer learnings, data signals, and results back into model improvement cycles.
• Partner with AI researchers to translate improvements into usable capabilities.
• Work with Software to integrate model behavior into end-to-end product workflows.
• Debug model failures using traces, evaluations, and customer context.

Skills

Python

PyTorch

JAX

TensorFlow

Model training

Experiment design

Tools

Git

Docker

Job description

Lila Sciences is seeking Machine Learning Engineers to turn frontier model capabilities into reliable customer workflows. You will train, adapt, and evaluate models, build evaluation loops, and collaborate with AI researchers and software engineers to deploy end-to-end solutions.

The role bridges research and engineering with autonomy, offering the chance to shape production‑quality systems in a fast‑moving environment.