Enable job alerts via email!

Senior MLE - MLOps, Python, GCP, VertexAI, GKE

UPS Supply Chain Solutions

Chennai District

On-site

INR 12,00,000 - 18,00,000

Full time

Today
Be an early applicant

Job summary

A global logistics company is seeking a skilled MLOps Engineer to manage machine learning pipelines in GCP. This role involves deploying models, ensuring reliability, and optimizing performance. Ideal candidates will have strong expertise in Python, SQL, and MLOps practices. The position offers the chance to work collaboratively across teams to drive machine learning initiatives that support business goals.

Qualifications

  • Expertise in programming languages like Python and SQL.
  • Understanding of Machine Learning concepts and algorithms.
  • Solid knowledge of model evaluation metrics.

Responsibilities

  • Managing the deployment of machine learning models in production.
  • Monitoring model performance using metrics.
  • Troubleshooting and resolving problems in production.

Skills

Python
SQL
MLOps best practices
Machine Learning concepts
Model monitoring tools
Communication skills
Ownership

Education

Bachelor’s Degree in a quantitative field

Tools

BigQueryML
Vertex AI
Kubernetes
Terraform
Job description
Job Description

Before you apply to a job, select your language preference from the options available at the top right of this page.

Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow—people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.

Job Summary

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 new 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.

Employee Type

Permanent

UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

Get your free, confidential resume review.
or drag and drop a PDF, DOC, DOCX, ODT, or PAGES file up to 5MB.