Machine Learning Operations Engineer Jobs

Retail Insight

Location:
United Kingdom, Richmond-Upon-Thames

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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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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Machine Learning Operations Engineer