Data Science Engineer Machine Learning

1 week ago

Paisley, Renfrewshire, United Kingdom Beeks Group Full time
About Beeks Group

We are 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 optimized 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.

We have a unique opportunity for a talented professional to join our R&D team as a ML Ops Engineer.

About the Role

The ML Ops Engineer will be part of a new team at Beeks Group with a focus on applying machine learning techniques to our real-time analytics product.

Key Responsibilities
  • Collaborate with in-house data science resource to develop and test models, algorithms with live and historical data, then establish best practices to scale up and productionize.
  • 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.
  • Optimize 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.
  • Design creative solutions to technical and business problems.
Requirements
  • 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.
  • Monitoring and performance optimization.
  • Data Processing expertise.
  • Working with modern databases – SQL, vector, time-series.
  • Experience with processing high volumes of live data.
What We Offer

We offer a competitive salary, a unique and highly rewarding Share Options scheme, a highly competitive pension scheme, life assurance cover, investment in Training, and Family cover Private Health Insurance.

We also offer a hybrid working arrangement, flexible work hours, and 33 days annual leave.

This is a full-time position.

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