Strong software engineering skills, emphasizing clean code and reliability.
Solid ML foundations and experience with the full ML lifecycle.
Prior experience training or fine-tuning models across various types.
Olympic athlete mindset focused on measurable improvement.
Proven resourcefulness in tackling engineering challenges.
Responsibilities
Build and maintain data preprocessing and generation pipelines.
Run end-to-end training and fine-tuning workflows.
Design and execute benchmarking/evaluation suites.
Collaborate with PhD researchers to operationalize models.
Clearly communicate results through metrics and dashboards.
Benefits
Competitive health, dental, and vision benefits covered by the company.
Flexible vacation policy to promote work-life balance.
Access to team-building activities and office meals.
401(k) plan offered for financial security.
Monthly stipends for wellness, fitness, commute, and AI tools.
Full Job Description
San Francisco | 5 Days Onsite
Location: Onsite in San Francisco
Compensation: Competitive Salary + Equity
About the Role
UniversalAGI is hiring an ML Engineer to help ship ML outcomes by owning the execution layer: data preprocessing/generation, training/fine-tuning, benchmarking, and delivering results.
What You'll Do
Build and maintain data preprocessing and data generation pipelines to support model training and evaluation.
Run training and fine-tuning workflows end-to-end and iterate quickly on performance improvements.
Design and execute benchmarking/evaluation suites to measure progress and customer outcomes.
Collaborate with PhD expert researchers to operationalize model architectures into repeatable, production-grade workflows.
Communicate results clearly (metrics, dashboards, short writeups) and maintain high-quality, reproducible work.
