MLOps Engineer

GlobalLogic
Greater London
5 months ago
Applications closed

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We are GlobalLogic, a Hitachi Group Company.


Based across 19 countries, GlobalLogic is a leader in digital engineering. We help brands across the globe design and build innovative products, platforms, and digital experiences for the modern world.


By integrating experience design, complex engineering, and data expertise – we help our clients imagine what’s possible and accelerate their transition into tomorrow’s digital businesses.

At GlobalLogic, we have a phenomenal track record of successfully delivering ground-breaking Cloud & Digital Transformation programmes and we have an international reach working with a wide variety of projects and customers. Our approach enables companies “build the exceptional” and be fit for purpose in the 21st century.


This role is based in our UK&I region.

About the role:

  • Responsible for developing software and pipelines to shorten the algorithm development life cycle from data curation to integration and deployment to support AI technologies that will help improve our users’ experience.
  • Develop continuous integration and deployment (CI/CD) pipelines on top of ML model infrastructure for multiple ML development teams.
  • Design and develop data engineering tools to store, manage, query and visualize big datasets.
  • Create data and metric visualization tools, web UI dashboards for model performance and data drift monitoring. AWS Sagemaker, Terraform


About you (ideally):

We hire based on personality, potential, and enthusiasm to make a difference, then we give you the tools and skills you need to follow your own path. You’ll benefit by gaining exposure to a wide range of tools and technologies that you can then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit.

  • Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management.
  • You’ll have strong experience deploying and productionising ML models
  • Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies.
  • Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems.


Technical Insight:

  • Skills with MLOps concepts and principles
  • Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes).
  • Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI)


Why work at GlobalLogic.

Our goal is to build an inclusive positive culture where everyone can feel comfortable being themselves, empowering our people to create their own high standards and therefore more value. We work together to promote fairness while recognising, valuing and embracing differences – providing a transparent support structure and generous training budget to help our people develop skills to progress their career. Our region also supports a hybrid model which can flex across a wide spectrum of working options determined by our business, customer and individual needs.


You’ll benefit from a comprehensive health and wellness plan, private healthcare (clinical and mental wellbeing), and discounted gym memberships. We offer a fantastic benefits package including a competitive pension scheme and recognition schemes through bonus/reward initiatives. Colleagues are entitled to an annual volunteering day – so you can take time to support a cause close to your heart. We also love to stay social at our trips to the zoo, quiz nights, sports events, theatre trips and much more.


We are an equal opportunities employer. It is our policy to promote an environment free from discrimination, harassment and victimisation. We are proud signatories to the Tech Talent Charter which was created because solving the diversity problem in tech requires a collective effort across companies and sectors - https://www.techtalentcharter.co.uk/.

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