Senior ML Engineer — Applied AI & Production

Aimlroles; United States; On-site; USD 180,000 - 298,000; Full time

Job summary

Lila Sciences is seeking Senior/Staff Machine Learning Engineers to advance Lila's AI models, focusing on training, evaluation, and production-oriented ML systems. You will turn frontier model capabilities into reliable workflows for real customer contexts and collaborate across AI Research and Software teams.

This role bridges research and engineering: training or adapting models, building evaluation loops, debugging model behavior, and delivering production-ready capabilities with autonomy and

Qualifications

• Experience building, training, adapting, or evaluating ML models.
• Strong Python and ML framework skills.
• Experience with Megatron-LM, TorchTitan, DeepSpeed, Ray.
• Ability to design experiments and evaluation metrics.
• Proven ability to bridge research and engineering teams.

Responsibilities

• Close the last-mile gap between model capabilities and customer workflows.
• Build evaluation loops to measure quality, reliability, and fit.
• Design experiments to improve model performance across use cases.
• Feed learnings and signals back into model improvement cycles.
• Partner with researchers to translate improvements into usable capabilities.
• Work with software to integrate model behavior into end-to-end workflows.
• Debug model failures using traces, evaluations, and customer context.
• Build reusable tooling for adaptation, evaluation, deployment.

Skills

Python

PyTorch

JAX

TensorFlow

Distributed training

Experiment design

Model debugging

Cross-functional collaboration

Tools

Megatron-LM

TorchTitan

DeepSpeed

Ray

Job description

Lila Sciences is seeking Senior/Staff Machine Learning Engineers to advance Lila's AI models, focusing on training, evaluation, and production-oriented ML systems. You will turn frontier model capabilities into reliable workflows for real customer contexts and collaborate across AI Research and Software teams.

This role bridges research and engineering: training or adapting models, building evaluation loops, debugging model behavior, and delivering production-ready capabilities with autonomy and