Senior – MLE – Python, ML Frameworks, MLOps, Containerization, Terraform, GCP, Vertex AI, IBM Watsonx
UPSIndiana, United States
Posted September 29, 2025
Full Time
About the Company
Operating in more than 200 countries and territories, we’re committed to moving our world forward by delivering what matters. Beginning as a small messenger service, UPS was started by two enterprising teenagers and a $100 loan. Now, we’re almost 500,000 UPSers strong, with operations around the globe. As a transportation and logistics leader, we are proud to offer innovative solutions to our customers—both big and small. We also support the communities we serve. Just take a look at The UPS Foundation’s social impact report! Headquartered in Atlanta, we can be found on the web at ups.com and about.ups.com. Job seekers can visit upsjobs.com to learn more. Our active social media channels include Facebook, Instagram, Twitter, YouTube, and TikTok. Facebook: www.facebook.com/ups Instagram: www.instagram.com/ups/ Twitter: www.twitter.com/ups TikTok: UPS YouTube: www.youtube.com/ups Website https://about.ups.com/ The UPS Foundation’s social impact report: https://about.ups.com/us/en/social-impact/reporting/the-ups-foundations-social-impact-report.html Career Site upsjobs.com
Job Description
We are seeking passionate Senior Machine Learning Engineers to design, develop, and deploy ML models and pipelines that drive business outcomes.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus)
- 5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems
- Strong foundations in data structures, algorithms, and distributed systems
- Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL
- Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML)
- Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow)
- Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management
- Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop)
- Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)
- Strong understanding of statistical methods, ML algorithms, and deep learning architectures
Benefits
- Generous Paid Time Off
- 401k Matching
- Retirement Plan