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Software Engineering

Staff Machine Learning Engineer

Long Beach, CA

Hybrid Full time

$240,000 to $306,000 a year

The employer is a developer-tools company making it easier for engineering teams to ship reliable software.

Our Long Beach office is growing, and we need a Staff Machine Learning Engineer who can set technical direction from day one. You will work closely with a collaborative software engineering group and report to the software engineering manager. This is a full-time, permanent position. This role is hybrid, with three days a week in our Long Beach office.

What you’ll do

  • Work with data scientists to move prototypes into reliable systems
  • Optimize model latency and serving cost
  • Train, evaluate and deploy machine learning models into production services
  • Design offline and online experiments to measure model impact
  • Build feature pipelines and model monitoring
  • Mentor junior engineers and review their work
  • Set technical standards and guide decisions across multiple projects

What you’ll bring

  • Bachelor’s degree in Computer Science, Machine Learning or a related field
  • 8+ years of relevant professional experience
  • Strong Python and software engineering fundamentals
  • Solid understanding of statistics and model evaluation
  • Experience deploying ML models to production
  • A track record of leading projects from scope through delivery

Nice to have

  • Experience with large language models or retrieval systems
  • Graduate degree in a quantitative field

Compensation and benefits

The pay range for this position in Long Beach, CA is $240,000 – $306,000 per year. Final pay depends on experience, skills and qualifications.

  • Annual performance bonus
  • Wellness stipend
  • Paid time off plus paid company holidays
  • Annual professional development and certification budget
  • Life insurance
  • Employee assistance program

The employer is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

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