Mlops

Responsibilities:

- Design and Implement MLOps Infrastructure: Build and maintain robust MLOps workflows using Azure Machine Learning and other Azure services to automate machine learning lifecycle from data preparation to model deployment and monitoring.
- Collaborate with Cross-Functional Teams: Work closely with data scientists, software developers, and IT specialists to ensure seamless integration and deployment of ML models into production.
- Continuous Monitoring and Optimization: Monitor the performance of machine learning models in production, identify issues with model drift, and optimize them for performance and scalability.
- Data Governance and Security: Implement and enforce data governance and security policies compliant with industry standards, ensuring data integrity and privacy.
- Research and Development: Stay abreast of the latest developments in MLOps technologies and Azure services. Evaluate and adopt new tools and practices to improve the deployment process and model performance.
- Mentorship and Leadership: Provide guidance and mentorship to junior MLOps engineers and team members, fostering a culture of learning and continuous improvement.

Qualifications:

- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
- Professional Experience: Minimum of 6 years of experience in a role focusing on machine learning, data engineering, or software development, with at least 3 years dedicated to MLOps.
- Technical Skills: -Proficiency in Azure Machine Learning, Azure Data Factory, Azure Databricks, and other relevant Azure services.
- Strong experience in automating and orchestrating ML workflows at scale.
- Knowledge of Python, SQL, and other scripting languages commonly used in data processing.
- Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
- Experience with CI/CD tools and practices in a machine learning context.

**Job Type**: Temporary
Contract length: 6 months

Pay: ₹1,200,000.00 - ₹1,400,000.00 per year

**Benefits**:

- Paid time off

Schedule:

- Day shift
- Fixed shift

Supplemental pay types:

- Performance bonus

**Experience**:

- total work: 4 years (required)

Work Location: Remote