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Machine Learning Systems Engineer, Model APIs

Anthropic is seeking a Machine Learning Systems Engineer to work with their Model APIs team, building systems that support researchers in evaluating AI models and conducting inference tasks.

Skills

  • Software engineering
  • Data infrastructure
  • Cloud infrastructure (AWS, GCP)
  • Python programming
  • Collaboration and communication
  • Scalable system design

Responsibilities

  • Design and maintain Model Evaluations infrastructure
  • Develop and optimize APIs for Research Inference
  • Create scalable data pipelines
  • Implement monitoring and optimization for inference systems
  • Build tools for researchers to analyze evaluation workflows
  • Collaborate with research teams to translate needs into solutions
  • Participate in on-call rotation and deliver operationally ready code

Education

  • Bachelor's degree in a related field or equivalent experience

Benefits

  • Competitive compensation
  • Equity donation matching
  • Generous vacation and parental leave
  • Flexible working hours
  • Collaborative office space
To read the complete job description, please click on the ‘Apply’ button
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Average salary estimate

$352500 / YEARLY (est.)
min
max
$300000K
$405000K

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Anthropic is an AI startup public-benefit company dedicated to AI safety and research, aiming to develop dependable, interpretable, and controllable AI systems. The company was was founded by former members of OpenAI in 2021.

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BADGES
Badge ChangemakerBadge Future MakerBadge InnovatorBadge Work&Life Balance
CULTURE VALUES
Inclusive & Diverse
Diversity of Opinions
Collaboration over Competition
Transparent & Candid
Passion for Exploration
Rapid Growth
Social Impact Driven
Mission Driven
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Vision Insurance
Maternity Leave
Paternity Leave
Paid Time-Off
Equity
401K Matching
Commuter Benefits
Learning & Development
WFH Reimbursements
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
INDUSTRY
TEAM SIZE
SALARY RANGE
$300,000/yr - $405,000/yr
EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
March 13, 2025

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