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AI/ML Engineer
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About The Company
Sainsbury’s is a leading retail organization committed to providing exceptional products and services to its customers. With a rich history of innovation and customer focus, Sainsbury’s operates a wide network of stores and an extensive online platform, serving millions of customers daily. The company values diversity, inclusion, and sustainability, striving to create a positive impact on communities and the environment. As a modern retailer, Sainsbury’s invests heavily in technology and data-driven solutions to enhance customer experience, streamline operations, and maintain its competitive edge in the retail sector.
About The Role
We are seeking a talented and dedicated Machine Learning Engineer to join our Data Science and Engineering team. In this role, you will be responsible for building, maintaining, and optimizing the infrastructure that supports the deployment of machine learning models across our products and services. You will work closely with Data Scientists, Data Analysts, and senior engineers to operationalize models, ensure their reliability, and enhance system performance. This position offers an exciting opportunity to contribute to innovative projects involving AI, automation, and scalable data solutions, directly impacting the customer experience and operational efficiency at Sainsbury’s.
Qualifications
- Proficiency in Python frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience with cloud platforms (AWS and/or Azure)
- Containerization skills with Docker
- Knowledge of DevOps tools, including GitHub Actions for CI/CD pipelines
- Experience with orchestration tools like Apache Airflow
- Infrastructure as code expertise with Terraform
- Strong understanding of software engineering best practices, including version control (Git), testing, and documentation
- Familiarity with MLOps lifecycle, including experimentation, deployment, and monitoring of ML models
- Data engineering fundamentals, including building data pipelines and integrating with data platforms (DBT, Kafka)
- Experience in incident response and troubleshooting complex systems
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Responsibilities
- Build and maintain production-grade ML pipelines and infrastructure, ensuring reliable deployment and operation of models
- Implement ML systems following architectural standards and making informed technical decisions
- Collaborate with Data Scientists and Data Analysts to operationalize models, translating experimental code into scalable solutions
- Contribute to MLOps practices, including CI/CD, model versioning, monitoring, and alerting systems
- Optimize ML system performance through resource management and performance tuning
- Participate in code reviews, knowledge sharing, and documentation efforts to enhance team capabilities
- Identify and address technical debt, performance bottlenecks, and operational issues proactively
- Respond to incidents affecting ML systems, supporting diagnosis and resolution of issues
- Stay updated on emerging trends and tools in ML engineering to continuously improve systems and practices
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Benefits
- 10% colleague discount at Sainsbury’s, Argos, TU, and Habitat after 4 weeks, increasing to 15% on specific days
- Participation in the company’s pension scheme and life cover options
- Performance-related bonus potential of up to 10% of salary
- Annual holiday allowance with options to buy additional leave
- Season ticket loans, cycle to work scheme, and health cash plans
- Pay advance options and access to discounts from numerous retailers
- Employee assistance program for wellbeing support
- Up to 26 weeks’ pay for maternity or adoption leave and up to 4 weeks’ pay for paternity leave
Equal Opportunity
Sainsbury’s is committed to fostering an inclusive and diverse environment. We welcome applications from all qualified candidates regardless of gender, age, ethnicity, disability, sexual orientation, or background. We believe that a diverse workforce enhances our ability to serve our customers and innovate effectively. We are dedicated to providing equal employment opportunities and ensuring a workplace where everyone feels valued, respected, and empowered to succeed.
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