Added
10 days ago
Type
Full time
Salary
Salary not provided

Related skills

python kubernetes ci/cd mlops ml
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πŸ“‹ Description

  • Build, maintain, and evolve scalable ML infra for model development, training, evaluation
  • Design reliable ML pipelines, platforms, and tooling for large-scale workloads.
  • Partner with ML engineers and researchers to productionize models.
  • Develop automation, testing, observability, reproducibility, data lineage, and governance across ML
  • Evaluate new data sources, technologies, platforms, and tools to improve performance and efficiency.
  • Collaborate with software, technology, product, and commercial teams to deliver ML solutions.

🎯 Requirements

  • Senior-level backend software engineering with strong ML understanding and interest in deep ML
  • Experience designing and maintaining ML infra, platforms, and tooling for large-scale training
  • Strong Python proficiency and experience with ML tooling (experiment tracking, version control
  • Hands-on MLOps experience (CI/CD, model monitoring, reproducibility, data lineage, governance
  • Cloud-native tech, Kubernetes, distributed computing, and scalable infra for ML workloads.
  • Understanding of AI concepts and practical use of AI tools, coding assistants, and LLM-based agents

🎁 Benefits

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