ML Platform Engineer Donaldson India Filter Systems

2.0 - 5.0 years

10 - 15 Lacs

gurugram

Work from Office

Key Responsibilities Collaborate with data scientists to convert experimental ML and GenAI workflows into scalable, production-ready pipelines. Co-develop and maintain shared, version-controlled repositories with modular components. Design and manage CI/CD pipelines using Azure DevOps for deploying ML models and GenAI tools. Containerize applications using Docker and deploy them using cloud-native services. Automate deployment workflows and infrastructure setup using Terraform and schema management tools for Azure and Snowflake. Ensure smooth integration of model training, evaluation, and deployment stages across projects. Deploy and manage GenAI solutions including chatbots, RAG applications, and predictive analytics tools. Operationalize LLMs and GenAI agents, including prompt orchestration and chaining logic. Track model versions, prompt iterations, and performance metrics to support continuous improvement. Implement observability tools to monitor latency, token usage, hallucination rates, and user feedback. Ensure compliance with internal governance policies around data security and ethical AI. Set up alerting and rollback mechanisms to handle model or infrastructure failures. Participate in code reviews and knowledge sharing sessions. Participate in and plan/suggest improvement to the existing workflows that impact business and technical domains. Key Qualifications & Requirements Specific academic or professional qualifications/experience/competence necessary for this position Education Qualification: Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related field. 2-3 years of experience in ML engineering, MLOps, platform engineering or DevOps role with exposure to Gen AI/ML workflows. Technical Competence & Skills: Strong proficiency in Python, Bash, and scripting for automation & CI/CD tools. Hands-on experience with CI/CD tools (Azure DevOps preferred) Experience with Docker and cloud-native services (Azure & Snowflake preferred). Leadership Competence: Strong problem solving & debugging skills Excellent communication & collaboration abilities Willingness to learn, experiment & contribute to evolving practices

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