San Francisco | 5 Days Onsite
Location: Onsite in San Francisco
Compensation: Competitive Salary + Equity
About the RoleUniversalAGI 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.
Qualifications- Strong software engineering skills (clean code, debugging, reliability, reproducibility).
- Solid ML foundations and hands-on experience with the ML lifecycle: data 12 training/fine-tuning 12 evaluation/benchmarking.
- Prior experience training or fine-tuning models (any modality/type - LLMs, computer vision, physics, surrogate models, etc.)
- Olympic athlete mindset: You have high standards for yourself and are obsessed with measurable improvement on the metrics you are delivering.
- Resourcefulness: you know when to do the "quick & correct" fix vs. when to invest in a robust solution, and you can justify the tradeoff with impact/
- Ownership: Comfortable owning work end-to-end and being accountable for measurable outcomes.
Bonus Qualifications- Experience building data pre-processing pipelines for training ML models.
- Experience with benchmarking methodology, experiment design, and metric selection.
- Familiarity with distributed training / scalable compute workflows.
- Experience in an FDE-style / delivery execution role (or similar "ship results fast" environments).
Cultural Fit- Technical Respect: Ability to earn respect through hands-on technical contribution
- Intensity: Thrives in our unusually intense culture - willing to grind when needed
- Customer Obsession: Passionate about solving real customer problems, not just publishing papers
- Deep Work: Values long, uninterrupted periods of focused work over meetings
- High Availability: Ready to be deeply involved whenever critical issues arise
- Communication: Can translate complex model decisions to customers and team
- Growth Mindset: Embraces the compounding returns of intelligence and continuous learning
- Startup Mindset: Comfortable with ambiguity, rapid change, and wearing multiple hats
- Work Ethic: Willing to put in the extra hours when needed to hit critical milestones
- Team Player: Collaborative approach with low ego and high accountability
- Bias for Action: Ships experiments fast, learns from failures, and iterates quickly
What We Offer- Opportunity to define the future of physics AI from the ground up
- Work on cutting-edge problems at the intersection of deep learning and physics simulation
- Direct collaboration with the founder & CEO and ability to influence company strategy
- Competitive compensation with significant equity upside
- In-person first culture - 5 days a week in office with a team that values face-to-face collaboration
- Access to world-class investors and advisors in the AI space
BenefitsWe provide great benefits, including:
- Competitive compensation and equity.
- Competitive health, dental, vision benefits paid by the company.
- 401(k) plan offering.
- Flexible vacation.
- Team Building & Fun Activities.
- Great scope, ownership and impact.
- AI tools stipend.
- Monthly commute stipend.
- Monthly wellness / fitness stipend.
- Daily office lunch & dinner covered by the company.
- Immigration support.
