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!

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or circumstances, with an equitable chance to achieve the careers

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