Job Description

  • Full-stack AI/ML experience (data ingestion through model deployment and maintenance).
  • Strong analytical mindset with a bias towards skeptical, data-driven decision-making.
  • Familiarity with cloud platforms (AWS, Azure, or GCP) for large-scale training and deployment.
  • Ability to communicate technical concepts to both experts and laypersons.
  • Knowledge of Agile or similar software development methodologies
  • Design and implement high-impact AI/ML models and workflows, ability to work on Cloud architectures and build solutions, ensuring scalability and reliability on cloud platforms such as Databricks, VertexAI, etc.
  • Collaborate with cross-functional teams (Data Engineering, ML Engineering, DevOps) to create holistic MLOps pipelines, leveraging frameworks such as MLflow and Kubeflow.
  • Conduct thorough reviews of ML models for performance, bias, and drift, proposing corrective actions. 
  • Integrate AI (including TimeSeries,...
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