Ml Engineer

Job Description:

Designation: Sr. MLOps Engineer Location: Hyderabad

Advanced Analytics Center

Role Value Proposition

Bridging the gap between machine learning and operational excellence within a Advanced Analytics team. By automating the deployment, monitoring, and maintenance of machine learning models, this role ensures that data-driven insights are seamlessly integrated into business processes. Collaboration with data scientists and engineers, the ML Ops Engineer enhances model performance, scalability, and reliability. Drive efficiency and innovation, fosters a culture of continuous improvement, enabling the organization to leverage machine learning for data decision-making.

Job Responsibilities

• Evaluate and source appropriate cloud infrastructure solutions for machine learning needs, ensuring cost-effectiveness and scalability based on project requirements.
• Automate and manage the deployment of machine learning models into production environments, ensuring version control for models and datasets using tools like Docker and Kubernetes.
• Set up monitoring tools to track model performance and data drift, conduct regular maintenance, and implement updates for production models.
• Work closely with data scientists, software engineers, and stakeholders to align on project goals, facilitate knowledge sharing, and communicate findings and updates to cross-functional teams.
• Design, implement, and maintain scalable ML infrastructure, optimizing cloud and on-premise resources for training and inference.
• Document ML processes, pipelines, and best practices while preparing reports on model performance, resource utilization, and system issues.
• Provide training and support for team members on ML Ops tools and methodologies, and stay updated on industry trends and emerging technologies.
• Diagnose and resolve issues related to model performance, infrastructure, and data quality, implementing solutions to enhance model robustness and reliability.

Education, Technical Skills & Other Critical Requirement

• 3-6 years of relevant experience in AI/ analytics product & solution delivery
• Bachelors/Masters degree in an information technology/computer science/ Engineering or equivalent fields experience.
• Proficiency in frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong skills in Python and/or R; familiarity with Java, Scala, or Go is a plus.
• Experience with cloud services such as AWS, Azure, or Google Cloud Platform, particularly in ML services (e.g., AWS SageMaker, Azure ML). Databricks is a must have.
• CI/CD tools (e.g., Jenkins, GitLab CI), containerization (e.g., Docker), and orchestration (e.g., Kubernetes).
• Experience with databases (SQL and NoSQL), data pipelines, ETL processes, ML pipeline orchestration (Airflow)
• Familiarity with monitoring and logging tools such as Prometheus, Grafana, or ELK stack.
• Proficient in using Git for version control.
• Strong analytical and troubleshooting abilities to diagnose and resolve issues effectively.
• Good communication skills for working with cross-functional teams and conveying technical concepts to non-technical stakeholders.
• Ability to manage multiple projects and prioritize tasks in a fast-paced environment.

Preferred:

• Familiarity of new age AI and ML techniques such as GenAI, foundational models, large language models (LLMs) and applications
• Relevant certifications in cloud platforms, machine learning, or data science (e.g., AWS Certified Machine Learning, Azure Data Engineer).
• Prior experience in MlOps
• Prior experience in P&C Insurance