About the company
Our client is a fast-growing software company.
The role
Raydar is recruiting for this role on behalf of our client. Own and scale the systems that train and run machine learning models in production, partnering with researchers so new models ship quickly and dependably. This is an individual contributor role for a versatile engineer who understands how models behave under load and can improve speed, stability and spend.
What you'll do
- Run and enhance the production systems that deliver model predictions, with a focus on latency, observability and uptime.
- Set up and refine training environments for models across a broad range of sizes.
- Develop logging, metrics and alerting across the machine learning stack.
- Create internal data pipelines and tools that shorten the path from research experiment to production release.
- Design infrastructure that distributes workloads across several cloud vendors, balancing quality, response time and cost.
Requirements
What we're looking for
- 3+ years of experience in machine learning infrastructure.
- Proven track record operating production model deployment systems in a demanding, high-performing engineering team.
- Strong Python skills and systems engineering experience with Kubernetes.
- Deep expertise in diagnosing GPU performance limits, tuning model deployment and monitoring.
- Comfort working in a fast-paced startup environment.
Bonus points
- Hands-on experience with training and deployment on a small number of machines.
- Prior work at a startup that develops its own models.
- Technical degree from a leading program.
- Research publications at top machine learning venues.
- Open source contributions in machine learning tooling.
- Strong results in math or computer science competitions.
Benefits
Compensation and benefits
- Base salary: USD 200,000 to 300,000 per year
- Equity
- Health, dental and vision coverage
- Parental leave
- Flexible time off
Location and work model
- San Francisco, California, United States
- On-site, 5 days per week in office
- Full-time
Skills Required
- 3+ years of experience in machine learning infrastructure
- Experience operating production model deployment systems in a demanding engineering team
- Strong Python skills
- Systems engineering experience with Kubernetes
- Expertise diagnosing GPU performance limitations
- Experience tuning model deployment and monitoring
- Comfort working in a fast-paced startup environment
- Hands-on experience with training and deployment on a small number of machines
- Prior experience at a startup developing its own machine learning models
- Technical degree from a leading program
- Research publications at leading machine learning venues
- Open source contributions to machine learning tooling
- Strong results in mathematics or computer science competitions
What We Do
Raydar is a talent acquisition and business consulting firm that connects world-class and emerging talent with growing organizations. It supports companies through team development, strategic hiring, and customized growth solutions, helping clients recruit roles such as engineers, product managers, executives, legal counsel, and quantitative traders. Raydar focuses on understanding each organization’s needs, culture, and long-term goals to build high-impact teams.
