Senior MLOps Engineer

Senior

Mandatory Skills:

• Python Programming:

• Expert in OOPs concepts and testing frameworks (e.g., PyTest)
• Strong experience with ML/DL libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Prophet, NumPy, Pandas)

• MLOps & DevOps:

• Proven experience in executing data science projects with MLOps implementation
• CI/CD pipeline design and implementation
• Docker (Mandatory)
• Experience with ML lifecycle tracking tools such as MLflow, Weights & Biases (W&B), or cloud-based ML monitoring tools
• Experience in version control (Git) and infrastructure-as-code (Terraform or CloudFormation)
• Familiarity with code linting, test coverage, and quality tools such as SonarQube

• Cloud & Orchestration:

• Hands-on experience with AWS SageMaker or GCP Vertex AI
• Proficiency with orchestration tools like Apache Airflow or Astronomer
• Strong understanding of cloud technologies (AWS or GCP)

• Software Engineering:

• Experience in building backend APIs using Flask, FastAPI, or Django
• Familiarity with distributed systems for model training and inference
• Experience working with Feature Stores
• Deep understanding of the ML/DL lifecycle from ideation, experimentation, deployment to model sunsetting
• Understanding of software development best practices, including automated testing and CI/CD integration
• Agile Practices:
• Proficient in working within a Scrum/Agile environment using tools like JIRA
• Cross-Functional Collaboration:
• Ability to collaborate effectively with product managers, domain experts, and business stakeholders to align ML initiatives with business goals

Preferred Skills:

• Experience building ML solutions for: (Any One)
• Sales Forecasting
• Marketing Mix Modelling
• Demand Forecasting
• Certified in machine learning or cloud platforms (e.g., AWS or GCP)
• Strong communication and documentation skills