MLOPS Engineer

Role: MLOps Engineer

Location: Hyderabad, Telangana, India

Interview Mode: In Person

Interview Date: Scheduled Interview

Key Skills and Technologies

• Cloud ML Platforms: AWS SageMaker, Azure ML Studio, GCP Vertex AI
• Big Data & Processing: PySpark, Azure Databricks
• MLOps Tools: MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline
• Orchestration & Infrastructure: Kubernetes, AKS, Terraform, Fast API

Core Responsibilities

• Model Deployment, Monitoring, and Retraining
• Design and implement Deployment, Inference, Monitoring, and Retraining pipelines
• Implement Drift Detection for Data and Model drift
• Manage Experiment Tracking
• Contribute to MLOps Architecture design
• Develop and publish REST APIs for ML models

Job Responsibilities

• Research and implement MLOps tools, frameworks, and platforms for Data Science projects.
• Work on initiatives to enhance the organization's MLOps maturity.
• Proactively introduce modern, agile, and automated approaches to Data Science.
• Conduct internal training and presentations on MLOps tools, their benefits, and usage.

Required Experience and Qualifications

• Extensive experience with Kubernetes.
• Proven experience in operationalizing Data Science projects (MLOps) using popular frameworks or platforms such as Kubeflow, AWS SageMaker, Google AI Platform, Azure Machine Learning, DataRobot, or DKube.
• Solid understanding of Machine Learning (ML) and Artificial Intelligence (AI) concepts, with hands-on experience in ML model development.
• Proficiency in Python for both ML tasks and automation. Strong knowledge of Bash and Unix command-line tools.
• Experience in implementing CI/CD/CT pipelines.
• Experience with cloud platforms, with a preference for AWS, is advantageous.