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Job Title

Machine Learning Engineer – Infrastructure & Training

Salary

$200,000 – $300,000 + equity

Location

New York City or San Francisco (on-site)

Responsibilities

• Design and manage scalable infrastructure to support training and deployment of large-scale ML models
• Optimize cloud-based compute environments (AWS, GCP) for distributed training workloads
• Monitor and improve system performance for high-throughput video and generative model tasks
• Use orchestration tools (e.g., Kubeflow, Docker) to streamline ML pipelines
• Collaborate with research and engineering teams to align compute systems with model training needs
  
  

Requirements

• Bachelor's degree in CS, IT, or related field
• Hands-on experience with AWS, GCP, or Azure for large-scale ML workloads
• Strong understanding of distributed training and multi-GPU scaling
• Familiarity with Docker and orchestration tools like Kubeflow
• Proficient in Python or Bash for automation and system management
• Excellent problem-solving and communication skills
• Prior experience in fast-paced, startup environments is a plus
  
  

Benefits

• Fully Covered Medical, Dental, and Vision Insurance
• Paid Time Off
• Parental Leave
• Free Lunches
• Team Building Events
• Collaborative Team environment
  
  

If you are interested in learning more about this position or any other roles we may have open, please apply today!

Accessibility Statement

• Read and apply for this role in the way that works for you by using
• our Recite Me assistive technology tool. Click the circle at the bottom right side of the screen and select your preferences.
• We make an active choice to be inclusive towards everyone every day.
• Please let us know if you require any accessibility adjustments through the application or interview process.
  
  

Our Commitment To Diversity, Equity, And Inclusion

Signify's mission is to empower every person, regardless of their background

or circumstances, with an equitable chance to achieve the careers

they deserve. Building a diverse future, one placement at a time.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Staffing and Recruiting

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