Related skills
optimization python mlops deployment ml📋 Description
- Learn from ML engineers who transitioned to field engineering and customer impact.
- Work on real customer workloads on advanced GPU infra, onboarding and deployments.
- Review prior optimization work, evaluate strategies, and recommend improvements.
- Develop a structured optimization playbook and case studies.
- Present your work to leadership at the end of the engagement.
🎯 Requirements
- Currently pursuing or completed a Master's in CS/ML or related field.
- Strong Python skills with ML inference, optimization, benchmarking, or deployment.
- Solid background in ML model architecture.
- Ability to write code to build and debug ML models from scratch.
- Understanding of production ML: MLOps, orchestration, open-source models.
- Self-directed: break problems into milestones and drive to completion.
🎁 Benefits
- Hybrid role with SF office 4 days/week; remote day Tuesday.
- Health, dental, and vision coverage for you and dependents.
- Wellness and commuter stipends for select roles.
- 401k plan with 2% company match (USA employees).
- Flexible paid time off plan.
- Equal Opportunity Employer.
Meet JobCopilot: Your Personal AI Job Hunter
Automatically Apply to Engineering Jobs. Just set your
preferences and Job Copilot will do the rest — finding, filtering, and applying while you focus on what matters.
Help us maintain the quality of jobs posted on Empllo!
Is this position not a remote job?
Let us know!