Lead Machine Learning Cloud Architect

  • Contract
  • London
  • Posted 2 weeks ago

Zebra Technologies


Remote Work: Hybrid


At Zebra, we extend the edge of possibility by shaping the future of work on the front line—reinventing how businesses run and moving society forward.

We are a community of changemakers, innovators and doers who come together to deliver a performance edge to the front line of business. We develop new technologies and create new solutions with partners to help organizations act with greater visibility, connectivity, and intelligence—delivering better experiences for workers and those they serve.

Being a part of Zebra means being seen, heard, valued, and respected as you define your path to a fulfilling career. Here, you’ll have opportunities to learn and lead at a leading company, and you can channel your skills towards causes that you and the Zebra community care about, locally, and globally.

Together, we’ve only begun to define the edge of what’s possible—for our people, our customers, and the world.

Would you like to join a small, driven and growing team where you can leverage your data science/machine learning/ MLOps /DevOps experience to build highly impactful AI/CV solutions? If so, we have an exciting opportunity for you to join our team.

You will be hands-on in leading machine learning cloud architecture and its implementation within the CTO team of Zebra Technologies. You will be responsible for collaborating with project teams, ensuring the solution architecture creates delightful experiences for internal and external stakeholders.


  • Have a significant role in establishing ML strategy and architecture.

  • Design and implement robust, scalable , and highly available cloud-based solutions.

  • Effectively communicate with and influence key s takeholde rs across the enterprise , at all levels of organizations.

  • Be part of a high performing team developing and imple menting AI/CV algo rithms to solve complex problems and create unique solutions in retail, man ufacturing, transport and logi stics and healt hcare.

  • Optimize ML/AI delivery processes with cross-functional teams.

  • Identify opportunities and shape use-cases where AI/ML can be applied.

  • Promote ML technologies and patterns.

  • Stay updated on ML advancements and cloud offerings.

  • Guide AI/ML projects from inception to production.

  • Demonstrate expertise in software engineering fundamentals and best practices .

  • Provide technical leadership and mentorship .

  • Facilitate the development and deployment of proof-of-concept machine learning systems.

  • Collaborate with engineers who are producing edge-based solutions to maximize sharing of developed software assets and processes between cloud and edge.

  • Drive standards, procedures, and tools to accelerate ML Engineering projects.

  • Conduct architecture reviews and issue resolution .

  • Work in an agile envi ronment and evaluate pre-project ideas in terms of technical complexity, solution architecture , and estimated effort .


  • Bachelor’s degree in Computer Science, Software, or related field

  • Significant experience in architect or software engineering roles

  • Proficiency in cloud environments, preferably GCP, with modern techniques/tools

  • MLOps experience with deployment and monitoring focus

  • Industry expertise in Machine Learning (model development, distributed training, pipeline development, etc.)

  • Experience creating scalable platforms for internal/external users

  • Architecting Data Science/ML platforms with Enterprise, Big Data, Image, and Time Series data

  • Familiarity with RESTful API and event-driven architectures

  • Understanding of DevOps and MLOps tool chains, including low-latency ML model deployment

  • Proficiency in Python; C++ is a plusHands-on experience deploying ML/DL solutions using modern frameworks (Tensorflow, SNPE, OpenVino, Keras, PyTorch, scikit-learn)

    Bonus Skills:

    Familiarity with ML ecosystem tools (Hive, Cassandra, Lakehouse, etc.) for Data StorageExpertise in data curation and architecting for ML project support

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