Senior Ai/ml Fullstack Engineer - Av Ml Infra

General Motors Australia & New Zealand

Base: $170,600-$261,300; bonus: incentive pyy base...
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5+ years professional software engineering experience
Production-grade web application development
Scalable cloud infrastructure on gcp or azure
** General Motors (GM) is seeking a Senior AI/ML Full-Stack Engineer to design and build end-to-end software products for their Autonomous Vehicle Machine Learning Infrastructure team. The role involves extensive full-stack development, project ownership, and mentorship, with a strong emphasis on building scalable infrastructure to support cutting-edge AI and ML applications. **

Job Summary

  • This role focuses on developing infrastructure products that empower GM teams to perform machine learning and data science at scale rather than applying specific ML models.
  • The team builds end-to-end ML platforms supporting Embodied AI, Simulation, and Data Science across the organization.
  • GM offers a comprehensive benefits package including medical, dental, vision, retirement savings, and tuition assistance programs.

Matching Summary

Match Score: 75

** General Motors (GM) is seeking a Senior AI/ML Full-Stack Engineer to design and build end-to-end software products for their Autonomous Vehicle Machine Learning Infrastructure team. The role involves extensive full-stack development, project ownership, and mentorship, with a strong emphasis on building scalable infrastructure to support cutting-edge AI and ML applications. **

Salary

Base: $170,600-$261,300; Bonus: Incentive pay based on company and individual performance; Benefits: Medical, dental, vision, retirement, paid vacation, tuition assistance

Skills & Requirements

Must-have

  • 5+ years professional software engineering experience
  • Production-grade web application development
  • Scalable cloud infrastructure on GCP or Azure
  • Proficiency in Python, C++, or Golang
  • Relational and NoSQL database management

Nice-to-have

  • Experience with Kubeflow, Flyte, or Airflow
  • Kubernetes orchestration platform knowledge
  • Understanding of ML models and pipelines
  • Relevant academic publications
  • Startup mentality and adaptability

Key Requirements

  • Bachelor's, Master's, or Ph.D. in Computer Science or related field
  • 1+ years leading large-scale initiatives
  • Demonstrated ability to develop systems at scale

Work Rights

Not specified

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