Machine Learning Operations Strategist

2 days ago


Navi Mumbai, Maharashtra, India beBeeModel Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Job Title : Model Deployment Specialist

We are seeking an experienced professional to provide expert guidance and technical support for deploying machine learning models to a secure, scalable, and cloud-hosted environment. This role involves advising on infrastructure design, API deployment strategies, CI/CD pipelines for ML models, and best practices for operationalizing machine learning workflows.

  1. Review and assess the current ML model deployment setup to ensure seamless integration with existing systems.
  2. Recommend suitable cloud platforms and hosting strategies for ML models and APIs, taking into account scalability, reliability, and cost-effectiveness.
  3. Define and implement best practices for MLOps, including version control, monitoring, and retraining workflows to maintain high-quality ML models.
  4. Provide guidance on CI/CD pipeline design and automation for ML systems, ensuring efficient and error-free deployments.
  5. Advise on security, compliance, and data governance in cloud-based environments to protect sensitive information and meet regulatory requirements.
  6. Collaborate with engineering teams to integrate ML components into the overall platform, ensuring smooth communication and effective teamwork.
  7. Deliver documentation, processes, and recommendations for ongoing maintenance and scalability to ensure long-term success of ML projects.

Required Qualifications :

  • Proven experience in MLOps and cloud-based ML model deployment, with a strong track record of successful project delivery.
  • Strong knowledge of ML model serving frameworks (TensorFlow Serving, TorchServe, MLflow, Seldon, etc.) and ability to integrate them with various cloud platforms.
  • Hands-on experience with major cloud providers (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes).
  • Proficiency in DevOps tools and principles (GitLab CI/CD, Jenkins, etc.) applied to ML workflows, with a focus on automation and efficiency.
  • Familiarity with security, compliance, and data governance, with a strong understanding of regulatory requirements and industry standards.
  • Excellent communication skills for technical consultation and documentation, with the ability to convey complex ideas simply and effectively.


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