Added
10 days ago
Type
Full time
Salary
Salary not provided

Related skills

cloud docker python kubernetes ci/cd

πŸ“‹ Description

  • Build, maintain, and evolve scalable machine learning infrastructure supporting model development
  • Design reliable, cost-effective ML pipelines, platforms, and engineering tooling for large-scale
  • Partner with ML engineers and researchers to transition models from prototypes into
  • Develop automation, testing, observability, monitoring, reproducibility, data lineage, and
  • Evaluate and integrate new data sources, technologies, platforms, and tools to improve model
  • Collaborate with software engineering, technology, product, and commercial stakeholders to deliver

🎯 Requirements

  • Senior-level backend software engineering with strong ML understanding and interest in deeper ML
  • Experience designing, building, and maintaining ML infrastructure, platforms, and tooling for
  • Strong proficiency in Python and modern ML engineering tools, including deep learning frameworks
  • Hands-on experience with MLOps practices such as CI/CD, model monitoring, reproducibility, data
  • Proven experience with cloud-native technologies, Kubernetes, distributed computing environments
  • Understanding of AI concepts and practical experience using AI tools, coding assistants, and

🎁 Benefits

  • Opportunity to work on advanced ML, computer vision, geospatial analytics, and AI challenges.
  • Exposure to large-scale aerial and satellite imagery and property intelligence tech.
  • Work with modern cloud-native infrastructure, distributed computing, ML platforms, and AI-enabled
  • Contribute to responsible AI, model governance, security, and risk management practices.
  • Collaborative environment with ML engineers, researchers, software engineers, product teams, and
  • Professional growth through complex, high-impact ML infrastructure challenges.
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