Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
Job Title: MLOps Engineer
Location: London, UK (hybrid)
Employment type: Contract
Orion Innovation is seeking MLOps Engineers to join our team and play a key role in building and scaling platforms that support the entire lifecycle of state-of-the-art machine learning models. This role involves maintaining and improving the MLOps infrastructure that enables multiple teams to deliver innovative, production-ready AI solutions.
With millions of data points processed every day, this opportunity allows you to make a real impact by helping us accelerate machine learning capabilities and bring meaningful, real-world value to our users.
The ideal candidate will have strong technical expertise in Kubernetes, cloud technologies (AWS, GCP, or Azure), and automation frameworks, along with a passion for advancing machine learning infrastructure.
Job ResponsibilitiesEvolve and scale the MLOps platform to support high-throughput model inference and faster iteration cycles across teams.
Drive improvements in performance, automation, and testing pipelines.
Manage and optimize GPU-powered Kubernetes clusters for efficient orchestration and cloud-native readiness.
Contribute to system reliability and stability by participating in on-call rotations and proactive monitoring.
Research, evaluate, and implement cutting-edge MLOps tools and practices aligned with long-term cloud strategies.
Collaborate with ML engineers and product teams to align infrastructure with evolving project needs.
Mentor and share expertise in DevOps, cloud operations, and ML engineering best practices.
Extensive experience managing GPU-enabled Kubernetes clusters and distributed, scalable infrastructure.
Strong understanding of the machine learning lifecycle in production (experimentation, training, deployment, versioning, monitoring).
Proficiency in Python, Go, or similar programming languages, with experience building automation tools for ML workflows.
Proven experience supporting ML engineers and data scientists by building infrastructure that accelerates experimentation and deployment.
Hands-on expertise with CI/CD tools such as ArgoCD or GitHub Actions, especially for ML workflows.
Familiarity with monitoring and observability tools such as Prometheus, Grafana, and cloud-native stacks.
Experience in incident response and participation in on-call rotations.
Strong knowledge of Docker, containerized applications, and hybrid/cloud-native environments.
Solid hands-on experience with Infrastructure-as-Code (Terraform) in cloud environments.
A passion for cloud-native MLOps and enthusiasm for exploring emerging technologies.
A curious, self-driven mindset with eagerness to learn and grow professionally.
Experience with AWS (including SageMaker AI or Bedrock) is a plus.
Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
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