Software Engineer, Machine Learning

Scopely•San Francisco, CA
•$165,131 - $180,946•Remote

About The Position

Implement and maintain scalable infrastructure solutions for deploying Artificial Intelligence (AI) and Machine Learning (ML) models. Work closely with ML scientists to develop engineering solutions that integrate AI and ML models into products. Develop automation tools and processes to streamline model evaluation and deployment workflows. Optimize infrastructure performance to use resources efficiently and minimize latency in model inference. Implement and maintain monitoring and alerting systems that support the reliability and availability of ML infrastructure components. Troubleshoot ML infrastructure issues, collaborating with stakeholders to identify root causes and implement solutions. Participate in cross-functional meetings to understand requirements and design engineering solutions that meet product needs. Contribute to code reviews, design discussions, and architecture planning to maintain high software development standards. Telecommuting within the US is permitted pursuant to company policy.

Requirements

  • Master’s degree or foreign equivalent in Computer Science, Computer Engineering, or a related quantitative field.
  • One year of experience in the job offered, as a Software Developer, Software Engineer Intern, Applied Research Intern, Teaching Assistant, or a related occupation.
  • Academic training and/or experience in Python, Machine Learning, Generative AI, SQL, system programming, and cloud computing.

Responsibilities

  • Implement and maintain scalable infrastructure solutions for deploying AI and ML models.
  • Collaborate with ML scientists on engineering solutions to integrate AI and ML models into products.
  • Develop automation tools and processes for model evaluation and deployment workflows.
  • Optimize infrastructure performance for efficient resource utilization and low-latency model inference.
  • Implement and maintain monitoring and alerting systems for ML infrastructure reliability and availability.
  • Troubleshoot ML infrastructure issues, identify root causes with stakeholders, and implement solutions.
  • Participate in cross-functional meetings to understand requirements and design solutions that meet product requirements.
  • Participate in code reviews, design discussions, and architecture planning sessions.

Benefits

  • Healthcare benefits
  • Retirement benefits
  • Pet insurance
  • Paid holidays
  • Paid Scopely free days
  • Unlimited paid time off
  • Employees may be eligible for equity and bonuses
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