Job highlights

- Bachelor s Degree in a quantitative field of mathematics,computer science,physics,economics,engineering,statistics (operations research,quantitative social science,etc-),international equivalent,or equivalent job experience-

- Experience in setting up or supporting NLP,Gen AI,LLM applications with MLOps features- .

- Modernization of the applications whenever required

We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP)- In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems-

You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure- The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production-ready, reliable, and continuously improving- You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business-

Responsibilities:

- Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems-

- Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias-

- Troubleshoot and resolve problems, maintain documentation,



and manage model versions for audit and rollback-

- Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders-

- Optimization of the queries and pipelines-

- Modernization of the applications whenever required

Qualifications:

- Expertise in programming languages like Python, SQL

- Solid understanding of best MLOps practices and concepts for deploying enterprise level ML systems-

- Understanding of Machine Learning concepts, models and algorithms including traditional regression, clustering models and neural networks (including deep learning, transformers, etc-)

- Understanding of model evaluation metrics, model monitoring tools and practices-

- Experienced with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning Registry, Cloud Monitoring, Kubernetes, etc-

- Solid oral and written communication skills and ability to prepare detailed technical documentation of current and existing applications-

- Strong ownership and collaborative qualities in their domain- Takes initiative to identify and drive opportunities for improvement and process streamlining-

- Bachelor s Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc-), international equivalent, or equivalent job experience-

Bonus Qualifications:

- Experience in Azure MLOPS,

- Familiarity with Cloud Billing-

- Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features-

- Experience working in an Agile environment, understanding of Lean Agile principles-

📌 Senior Machine Learning Engineer (Chennai)
🏢 UPS Supply Chain Solutions (UPS
📍 Chennai