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Machine Learning Operations Engineer

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Retail Insight

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Location:
United Kingdom, Richmond-Upon-Thames

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

Turn Data into Action with Retail Insight. At Retail Insight (RI), we transform data into actionable strategies, empowering retailers and CPGs to make smarter decisions. Our cutting-edge algorithms and innovative retail execution products are trusted by many of the world’s leading companies to improve sales, profitability, and operational efficiency. From tackling out-of-stocks and poor in-store execution to reducing waste, markdowns, and shrink, RI helps businesses unlock performance drivers through advanced analytics. We’re looking for a MLOps Engineer to help us operationalize machine learning at scale. This is a critical role at the intersection of data science and IT operations, ensuring our ML models are robust, reliable, and production-ready. You’ll build the infrastructure, automation, and pipelines that enable seamless deployment and ongoing performance of ML systems — accelerating innovation and helping us deliver value faster to our clients.

Job Responsibility:

  • Build Pipelines: Design and maintain scalable ML pipelines that automate the end-to-end lifecycle
  • Deploy & Monitor Models: Oversee deployment into production, monitoring performance and retraining as needed
  • Automation & CI/CD: Implement CI/CD pipelines for ML workflows, driving speed and reliability
  • Manage Infrastructure: Develop and maintain infrastructure for data, models, and computation using cloud and containerization technologies
  • Collaborate Across Teams: Partner with Data Science, Engineering, Operations, and Product to deliver seamless ML solutions
  • Establish Best Practices: Promote MLOps standards to ensure quality, scalability, and consistency
  • Innovate & Improve: Continuously evaluate new tools and techniques to evolve our MLOps capabilities

Requirements:

  • Proven programming skills in Python, with experience in ML frameworks
  • Experience with cloud platforms (Snowflake, Azure, GCP, AWS)
  • Skilled in containerization (Docker) and orchestration (Kubernetes)
  • Knowledge of data engineering concepts (ETL, data warehousing, data lakes, databases)
  • Experience with CI/CD automation for ML workflows
  • Familiarity with monitoring and logging tools for production ML models
  • Ability to work in agile, cross-functional teams
  • Relevant degree in Computer Science, Data Science, Engineering, or related field (preferred)

Nice to have:

  • Experience in a retail background would be beneficial
  • Keen on continuous technical development, data analytics trends and tools
What we offer:
  • Flexible Working – Enjoy a hybrid work model (typically 2 days in the office) with flexibility based on business needs, plus a work from anywhere policy
  • Time Off – 25 days annual leave (+ bank holidays), increasing with length of service, plus an extra day off for your birthday
  • We also operate summer hours
  • Learning & Development – Access a vast range of courses through our learning platform and benefit from structured career progression plans
  • Health & Wellbeing – Private Medical Insurance, a healthcare cash plan, and mental health support via Help@Hand
  • Plus, we’ll ensure you have a safe and productive home setup with a workspace assessment
  • Giving Back – Take paid volunteer days to support your local community, donate to your chosen charity through salary sacrifice (we’ll match it!), and make a difference with Give as You Earn
  • Extra Perks – A car purchase scheme to make buying a new car easier, plus access to additional benefits through our online platform, including gym discounts

Additional Information:

Job Posted:
December 11, 2025

Employment Type:
Fulltime
Work Type:
Hybrid work
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