We are looking for a Senior MLOps Engineer to join our production team, focusing on generative AI and ML applications. The ideal candidate has expertise in Microsoft OpenAI, Domino Data Lab, and Mistral models and can optimize, deploy, and monitor ML models in production environments.

Key Responsibilities:

• Deploy and optimize machine learning and generative AI models in production.
• Manage ML infrastructure (cloud/on-premise), ensuring scalability and reliability.
• Build CI/CD pipelines for model deployment and automate ML workflows.
• Implement containerization (Docker, Kubernetes, OpenShift) for model packaging.
• Set up model monitoring, logging, and performance tracking.
• Ensure regulatory compliance with data protection standards.
• Collaborate with data scientists and application teams to improve ML operations.
• Document processes, methodologies, and model performance for transparency.

Required Skills:

• 7+ years of IT experience with a focus on MLOps.
• Hands-on experience with Azure, AWS, or GCP for ML model deployment.
• Expertise in ML frameworks (scikit-learn, TensorFlow, PyTorch, Keras).
• Proficient in Python, Bash, Go, or Ruby and working with Linux environments.
• Strong understanding of MLOps tools (Kubeflow, MLFlow, Airflow, DataRobot).
• Experience with IaC (Terraform, CloudFormation) and CI/CD pipelines.
• Knowledge of APIGEE API Management, model versioning, and performance tuning.
• Experience with Mistral models and generative AI tools.
• MLOps Certification or Domino Data Lab Certification.
• Working knowledge of Scrum/Agile methodologies.