Machine Learning Engineer

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Olive Jar Digital

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SaaS • B2B • Consulting

Olive Jar Digital is one of the UK’s fastest growing, award-winning digital consultancies, championing managed digital delivery services and the provision of expert talent to enhance your team, satisfying your user needs. They offer services in digital transformation, cloud computing, business intelligence, and data analytics. The company provides individual consultants or full agile teams with a wide range of specialist skills to fulfill diverse delivery needs. Olive Jar Digital is dedicated to helping businesses scale up by managing projects from discovery to live launch, ensuring quality and adherence to budget and timelines as part of a collaborative approach.

11 - 50 employees

Founded 2015

☁️ SaaS

🤝 B2B

📋 Description

• Build, refine, and optimise AI/ML prototypes, ensuring they meet quality, security, and performance standards. • Develop and maintain technical design documentation, including architecture, model pipelines, and integration patterns. • Implement automated deployment pipelines, CI/CD flows, unit/regression testing, and monitoring/telemetry for prototypes. • Deploy models into development and test environments and support iterative updates based on feedback. • Collaborate with data scientists on model integration, feature engineering, and evaluation frameworks. • Ensure codebases follow best practices in engineering, documentation, security, and accessibility. • Support playback sessions, technical reviews, and knowledge-transfer activities.

🎯 Requirements

• Strong experience as an ML Engineer or similar role within AI/ML product development. • Proficiency in building ML pipelines, APIs, cloud-based deployments, and automated testing. • Solid software engineering skills (e.g., Python, version control, CI/CD, cloud platforms). • Ability to work collaboratively with data scientists, engineers, and product teams. • Comfortable producing clear, structured technical documentation. • Experience with LLMs, vector databases, retrieval-augmented generation, or intelligent search. • Familiarity with MLOps tooling, containerisation, and cloud-native environments. • Exposure to rapid prototyping in Discovery/Alpha phases.

🏖️ Benefits

• 25 Days Annual Leave per annum (plus 8 Bank Holidays as standard) • Health Insurance • Pension Scheme • Annual Bonus Scheme • Annual Salary Review • Electric Car Scheme