About Beeks

Beeks Group is a leading managed cloud provider exclusively within the agile and fast-moving financial services and capital markets sector. Our Infrastructure-as-a-Service (IAAS) model is optimised for low-latency private cloud compute, connectivity and analytics, providing the flexibility to deploy and connect to Exchanges, trading venues and public cloud for a true hybrid cloud experience.

Founded in 2011, Beeks Group is listed on the London AIM Stock Exchange and has enjoyed continued growth each year. Beeks Group now employs over 100 team members across the globe and has an international network of over thirty data centres.

We have a fantastic opportunity for a ML Ops Engineer to join us at our unique Head Office in Renfrew, which includes our state-of-the-art gym with weekly circuit training, a personal trainer and yoga classes as well as the Beeks Bar or weekly masseuse to help you unwind!

About the role

The ML Ops Engineer will be part of a new R&D team at Beeks with a focus on applying ML techniques to our real time analytics product.

Responsibilities

• Working alongside in-house Data Science resource to develop and test models, algorithms with live and historical data, then establish best practices to scale up and productionise. 
• Design and implement scalable and reliable model deployment pipelines. 
• Build and maintain the ML infrastructure in-house and deployed to customers – with a focus on on-premise infrastructure rather than public cloud. 
• Develop and manage CI/CD pipelines for ML models to automate testing, validation, and deployment processes. 
• Implement monitoring and logging solutions to track model performance and system health. 
• Automate repetitive tasks related to data preprocessing, model training, and deployment. 
• Optimise the performance of ML models and systems for speed and scalability. 
• Ensure the security of data and models in all stages of the ML lifecycle. 
• Maintain comprehensive documentation of the ML pipeline, processes, and infrastructure. 
• Build out internal best practices for ML engineering and keep peers informed. 
• Keep up with the very rapidly evolving industry standards – ensuring the most appropriate methods and tools are used where possible. 
• Design creative solutions to technical and business problems. 

Skills & Experiences Required

• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field. 
• 3+ years of experience in a similar role, with hands-on experience in MLOps or DevOps. 
• Familiarity with data science and machine learning principles and workflows. 
• Proficiency in Python, familiarity with C++, Rust beneficial. 
• ML tooling experience – pandas, NumPy, PyTorch, Jupyter Notebooks 
• Working experience with Git 
• Production deployment expertise 
• Containerisation, orchestration 
• Monitoring and performance optimisation 
• CI/CD pipelines 
• Data Processing expertise 
• Working with modern databases – SQL, vector, time-series 
• Experience with processing high volumes of live data 

What we can offer you

Compensation & Benefits

• A competitive salary
• A unique and highly rewarding Share Options scheme
• Highly competitive pension scheme
• EV salary exchange scheme
• Life assurance cover
• Investment in Training
• Family cover Private Health Insurance

Lifestyle

• Hybrid working (3 days in the office / 2 days at home)
• Flexible work hours
• 33 days annual leave

This is a full-time position

We are an equal opportunity employer