People In AI ยท 2 days ago
MLOps Engineer
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Responsibilities
Build a cost-efficient platform to train, deploy, and monitor thousands of machine learning models.
Lead the integration of Databricks into AWS infrastructure to enhance data engineering and model development capabilities.
Develop and optimize MLOps pipelines to manage thousands of models with minimal human intervention.
Evaluate and implement feature stores like Databricks Feature Store or Feast to streamline ML workflows.
Enhance CI/CD pipelines using tools like GitHub Actions and Terraform for seamless deployments.
Build tools to track model performance, detect data drift, and optimize for efficiency and cost-effectiveness.
Work closely with data scientists, platform engineers, and DevOps teams to bridge gaps between data science and operations.
Qualification
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Required
5+ years in MLOps, Machine Learning Engineering, Data Engineering, or DevOps.
Proficient with AWS (especially SageMaker) and Databricks.
Strong Python skills; familiarity with ML frameworks like TensorFlow or PyTorch.
Experience with CI/CD tools and Infrastructure as Code (e.g., Terraform).
Knowledge of containerization and orchestration tools like Docker and Kubernetes.
Excellent problem-solving abilities, strong communication skills, and the ability to thrive in a fast-paced environment.
Company
People In AI
At People in AI, we specialize in staffing solutions for the rapidly expanding AI sector.
Funding
Current Stage
Early StageCompany data provided by crunchbase