Senior MLE - MLOps, Python, GCP, VertexAI, GKE
At a glance
Senior ML Platform & Ops role at Hcmportal. IN - TDC 1 (IN110) · full-time.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Deploy and maintain production ML models, connecting them to existing systems and keeping releases reliable
- Track accuracy, precision, recall and F1 scores, then investigate drift, bias or declining model results
- Review monitoring data for emerging issues and share model performance updates with stakeholders
- Resolve production problems, document changes, manage model versions, and improve queries and pipelines
- Modernize applications when needed and build automated ML workflows and CI/CD pipelines on GCP
What you bring
- You can program in Python and SQL and understand MLOps practices for enterprise machine learning systems
- You understand ML algorithms, including regression, clustering, neural networks and transformers, plus model evaluation and monitoring
- You have hands-on experience with GCP ML services such as BigQuery ML, Vertex AI Pipelines or another listed tool
- You hold a quantitative degree, or have equivalent work experience
- You communicate clearly and can produce detailed technical documentation for applications
Who this fits
This senior role suits someone who can own production ML operations and work with technical teams, architects and business stakeholders. You’ll need to take initiative, collaborate across teams and improve processes.
From the employer
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 Description:
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:
UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.