Title: ML & Data Ops Engineer

Location: Bangalore, India (Hybrid)

About the Role: EXL is seeking a skilled and experienced ML & Data Ops Engineer to join our team. This role is pivotal in ensuring the seamless deployment, monitoring, and maintenance of data pipelines and machine learning models in a production environment. You will collaborate with data engineers, data scientists, and IT teams to optimize workflows, resolve technical issues, and ensure efficient, reliable, and scalable data and ML operations.

Key Responsibilities:

• Data Pipeline Deployment: Collaborate with teams to deploy scalable and robust data pipelines and machine learning models into production environments using tools like Python, SQL, and PySpark.
• Model Versioning & CI/CD: Implement version control and manage CI/CD pipelines for data and ML deployment using tools like Jenkins, Concourse, Ansible, Chef, and Puppet.
• Orchestration & Automation: Integrate data pipelines with orchestration tools like Airflow and develop automation scripts for data ingestion, feature engineering, model training, and deployment.
• Monitoring & Optimization: Implement and automate monitoring and alerting systems to detect and address issues in data pipelines, machine learning models, and infrastructure. Identify and resolve performance bottlenecks.
• Security & Documentation: Implement security best practices and maintain detailed documentation for all data and ML operations processes, configurations, and updates.
• Client Communication & Collaboration: Own client communication, gather requirements, structure problems, and deliver solutions. Collaborate with cross-functional teams across onshore and offshore locations.
• Research & Development: Stay up to date with new tools and technologies, create PoVs on their fit within the ML Ops scope, and contribute to business development initiatives like RFP responses and building accelerators.
• Team Leadership: Build capabilities in junior team members and guide them in technical and operational excellence.

Required Qualifications:

• Technical Expertise: Advanced proficiency in Python and SQL, with hands-on experience in developing and deploying machine learning models and data pipelines. Familiarity with cloud platforms and tools like Apache Spark, Kafka, Docker, and Kubernetes.
• ML Frameworks: Strong understanding of machine learning concepts and frameworks such as TensorFlow, PyTorch, and Kubeflow.
• CI/CD & Version Control: Experience with version control systems like Git and CI/CD tools such as Jenkins, Concourse, Ansible, Chef, and Puppet.
• Automation & Orchestration: Proven experience in process automation, monitoring, alerting, and using orchestration tools like Airflow.
• Problem-Solving & Communication: Excellent problem-solving skills, with the ability to communicate complex technical concepts to both technical and non-technical stakeholders.