Added
7 days ago
Type
Full time
Salary
Salary not provided

Related skills

python kubernetes machine learning ci/cd mlops

πŸ“‹ Description

  • Build, maintain, and evolve scalable ML infrastructure for model development, training, evaluation
  • Design reliable ML pipelines, platforms, and tooling for large-scale workloads.
  • Partner with ML engineers to productionize models from prototypes.
  • Develop automation, observability, reproducibility, data lineage, and governance across ML
  • Evaluate new data sources, tech, platforms to improve performance and efficiency.
  • Collaborate with engineering, product, and business stakeholders to deliver ML solutions.

🎯 Requirements

  • Senior backend software engineer with strong ML understanding and interest in deeper ML expertise.
  • Experience building ML infrastructure, platforms, and tooling for large-scale training, evaluation
  • Strong Python proficiency with ML tooling, DL frameworks, experiment tracking, versioning
  • Hands-on MLOps: CI/CD, model monitoring, reproducibility, data lineage, governance, production ops.
  • Experience with cloud-native tech, Kubernetes, distributed computing for ML workloads.
  • Understanding of AI concepts and use of AI tools, coding assistants, and LLM agents to enhance

🎁 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 infra, distributed computing, ML platforms, and AI tools.
  • Contribute to responsible AI, model governance, security, and risk practices.
  • Collaborative environment with ML engineers, researchers, software engineers, product teams, and
  • Professional growth through complex ML infrastructure challenges.
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