Added
1 day ago
Type
Full time
Salary
Salary not provided

Related skills

docker python kubernetes 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/researchers to productionize models from prototypes.
  • Develop automation, observability, testing, data lineage, and governance across ML environments.
  • Evaluate new data sources and tools to improve model performance and efficiency.
  • Collaborate with software, product, and business stakeholders on scalable ML solutions.

🎯 Requirements

  • Senior-level backend software engineering with strong ML understanding and interest in ML expertise.
  • Experience designing and maintaining ML infrastructure for large-scale
  • Strong Python with ML tooling, experiment tracking, version control, containers, and automated
  • Hands-on experience with MLOps: CI/CD, monitoring, reproducibility, data lineage, governance
  • Cloud-native tech, Kubernetes, distributed computing, scalable ML infra.
  • Understanding of AI concepts; experience with AI tools, coding assistants, LLM agents to improve

🎁 Benefits

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