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Together, we can beat cancer.

At Varian, a Siemens Healthineers Company, we bring together the world’s best talent to realize our vision of a world without fear of cancer. Together, we work passionately to develop and deliver easy-to-use, efficient oncology solutions. If you want to be part of this important mission, we want to hear from you. 

We are looking for an experienced and enthusiastic Machine Learning Ops engineer well versed in design and implementation of AI/ML platforms and integrated workspaces built for data engineers, data scientists and machine learning engineers in the medical research field. The role calls for a person who is familiar with working in a fast-paced and highly collaborative research environment who also has a passion for automating tedious manual workflows. 


You will be working with a team of data engineers and software developers to support machine learning engineers and AI and data scientists. Your mission is to provide your data scientist and ML engineer colleagues with deterministic AI/ML development and experimentation environments with access to an elastic, distributed model training and inference infrastructure. 





  • Has experience in building and managing distributed compute infrastructure for AI/ML training at scale, and developing end-to-end ML pipelines with validation
  • Has strong programming background. Fluency in Python and shell scripting required 
  • Has strong background in PyTorch framework and ecosystem 
  • Has experience with using IaC tools such as Terraform and configuration automation tools such as Ansible
  • Has robust software engineering skills, and a track record of building custom tools that fit internal needs
  • Has experience using Docker and container orchestration technologies such as Kubernetes 
  • Experience developing systems on modern Linux environments. 
  • Experience in deployment and management of cloud native infrastructure and services with an emphasis on performance and cost optimization. Google Cloud experience preferred. 
  • 4-8 years of total experience in a combination of software development, DevOps and ML Ops fields 
  • At least one year of experience supporting machine learning and AI teams 
  • Bachelor’s degree in Computer Science or related fields (software engineering or equivalent) 





  • Master’s degree in Computer Science or related fields (software engineering or equivalent) 
  • Experience in configuration and troubleshooting of AI and machine learning tooling such as Jupyter notebooks, GCP AI Platform, GCP Vertex AI and Ray
  • Experience with deployment and performance optimization of network file share and distributed file storage systems 
  • Experience with homomorphic encryption and federated learning 
  • Working knowledge of major cryptographic protocols and authentication schemes such as TLS, x509, 802.1x, U2F, SAML. 
  • Experience supporting production lines, medical systems, and/or laboratory settings.


Cultural fit 

  • Inspires others: Shares passion for our vision, culture, and opportunity 
  • Collaborative: Builds partnerships and ensures shared success 
  • Curious: Motivated by discovery and exploration in research, technology, and solution delivery  
  • Accountable: Owns and keeps commitments
  • Data-driven: Balances data with intuition, embraces an experimental test and learn approach to make informed business decisions 
  • Results-oriented: Focuses on delivering results not activity
  • Business minded: Demonstrates strategic thinking, operational intelligence, and sound judgment
  • Courageous: Willing to make hard decisions in service of the business 

To ensure compliance with applicable legal requirements in the U.S., including the federal COVID-19 vaccination mandate, all U.S. employees must be fully vaccinated for COVID-19, subject to legally required and approved accommodations.