Analytics DevOps Engineer

About the Role: Analytics DevOps Engineer at HP - Pune, India

HP is seeking a skilled Analytics DevOps Engineer to join our team in Pune, India. This role is pivotal in ensuring the seamless operation and continuous improvement of our AI and Machine Learning initiatives. You will be instrumental in building, managing, and optimizing robust data pipelines, enhancing model performance, and automating deployment workflows through advanced CI/CD practices.

Key Responsibilities:

• Implement and maintain efficient data pipelines that support complex AI/ML workflows.
• Optimize the performance of machine learning models through meticulous tuning and ongoing monitoring.
• Automate the deployment of models and associated infrastructure using cutting-edge CI/CD tools.
• Proactively monitor the health of ML models, including drift detection and performance metrics, to ensure reliability.
• Collaborate closely with data scientists to ensure infrastructure perfectly aligns with model requirements and development cycles.
• Develop and maintain robust CI/CD pipelines specifically designed for the efficient deployment of ML models.
• Troubleshoot and resolve operational issues within AI/ML systems, ensuring minimal downtime.
• Uphold and apply best practices in version control and model reproducibility for a streamlined development process.
• Perform critical performance tuning of deployed systems to maximize efficiency and output.

Qualifications and Experience:

• 2-4 years of relevant professional experience.
• A Bachelor's degree in Engineering, Computer Science, Information Technology, or a closely related technical field.

Required Skills and Knowledge:

• Proficiency in CI/CD tools such as Azure Pipelines or GitHub Actions.
• Experience with workflow orchestration tools like Airflow.
• Strong software engineering skills, including Git, Python, R, Java, and Scala.
• Hands-on experience with containerization and orchestration technologies: Docker, Kubernetes, EKS, AKS.
• Familiarity with cloud platforms and services: AWS (SageMaker, Bedrock) or Azure ML / AI Foundry.
• Experience with Databricks for data analytics and machine learning.
• Solid understanding of data processing and transformation techniques.
• Experience with monitoring and logging tools (e.g., Splunk, OpenSearch, DataDog).
• Familiarity with project management tools like Jira.
• Knowledge of Machine Learning (ML) principles and practices.
• Expertise in MLOps (Machine Learning Operations).
• Strong Data Engineering capabilities.
• Experience in Model Deployment strategies and execution.
• Demonstrated ability in Performance Optimization of systems.
• Understanding of Artificial Intelligence (AI) concepts.
• Skills in Infrastructure Management.
• Proficiency in Monitoring and Observability techniques.
• Expertise in Continuous Integration (CI).

Desired Cross-Organizational Skills:

• Effective Communication
• Results Orientation
• Learning Agility
• Digital Fluency
• Customer Centricity