Staff ML Engineer — LLMs/MoEs, On-Device AI Lead

Webai; Austin (TX); Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Equity options

Wellness stipend

Education support

Job summary

webAI in Austin seeks a Staff Machine Learning Engineer with a strong background in Large Language Models and Mixture of Experts. You will lead core product initiatives across on-device inference optimization and related areas, delivering end-to-end features in collaboration with other engineering teams.

Applicants should have a Ph.D. or advanced degree, at least six years in ML, and a track record of publications or industry impact.

Qualifications

• Ph.D. or equivalent research experience preferred.
• Proven track record in ML model development and deployment.
• 6+ years of ML experience with LLMs/MoEs.
• Strong Python proficiency and ML framework experience.
• Ability to lead complex projects and mentor others.

Responsibilities

• Lead development and optimization of Large Language Models and Mixture of Experts models.
• Collaborate with cross-functional teams to integrate ML models into our platform.
• Conduct cutting-edge research to improve performance and efficiency of LLMs.
• Stay abreast of advances in AI/ML and apply them to improve models and methods.
• Mentor junior engineers and contribute to knowledge sharing.

Skills

Large Language Models

Mixture of Experts

Python

TensorFlow

PyTorch

On-device inference

Cross-functional leadership

Research & publications

Education

Ph.D. preferred

Tools

Docker

Kubernetes

AWS

Hadoop

Spark

Job description

webAI in Austin seeks a Staff Machine Learning Engineer with a strong background in Large Language Models and Mixture of Experts. You will lead core product initiatives across on-device inference optimization and related areas, delivering end-to-end features in collaboration with other engineering teams.

Applicants should have a Ph.D. or advanced degree, at least six years in ML, and a track record of publications or industry impact.