Added
6 days ago
Type
Full time
Salary
Salary not provided

Related skills

cloud docker python kubernetes ci/cd

πŸ“‹ Description

  • Build, maintain, scalable ML infrastructure for model lifecycle.
  • Design reliable ML pipelines and tooling for large-scale workloads.
  • Partner with ML engineers to productionize models from prototypes.
  • Develop automation, observability, data lineage, governance across ML envs.
  • Evaluate new data sources/tools to improve perf and efficiency.
  • Collaborate with stakeholders to deliver scalable ML solutions.

🎯 Requirements

  • Senior backend with ML understanding and interest to deepen ML expertise.
  • Experience building ML infra for large-scale training, eval, deployment.
  • Strong Python and ML tooling (DL frameworks, experiment tracking, containers, CI/CD).
  • Hands-on MLOps: CI/CD, monitoring, reproducibility, data lineage, governance, prod ops.
  • Cloud-native tech, Kubernetes, distributed infra for ML workloads.
  • PhD preferred; Master's with extensive experience or Bachelor's with hands-on.

🎁 Benefits

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