Machine Learning Engineer

RealityMine Limited; Stretford; Hybrid; GBP 40,000 - 60,000; Full time

Job summary

A data insights company located in Stretford is looking for a Machine Learning Engineer to design and deploy production-ready models and data pipelines. Responsibilities include collaborating with technical teams, optimizing performance for big data applications, and ensuring scalable ML solutions. The role offers a hybrid working model, generous time off, and a bonus scheme, making it ideal for candidates looking to make a significant impact in a dynamic environment.

Benefits

Generous Time Off

Life assurance

Bonus scheme

Cycle to Work Scheme

Budget for training programs

Support for local charities

Qualifications

• 2–3 years of production experience in machine learning systems.
• Experience handling large datasets and distributed processing.
• Comfort with deploying ML models into production environments.

Responsibilities

• Design, develop, and deploy machine learning models.
• Build and maintain data pipelines for ML inference.
• Collaborate with teams to integrate ML solutions into products.

Skills

Python

SQL

PyTorch

Big Data tools

AWS

MLflow

Job description

RealityMine has been a pioneer in delivering data driven insights to the world's largest brands for over a decade. Our platform provides unique data solutions to our clients enabling them to make strategic, informed decisions powered by data from real people, collected in a privacy safe way.

We are now looking for a Machine Learning Engineer to help build and optimise production‑ready machine learning systems and advance our data pipelines for inference at scale. This is a pivotal role for someone who thrives in autonomous environments and enjoys owning solutions from concept to deployment.

The Role:

As a Machine Learning Engineer, you will design, develop, and deploy models and pipelines that power RealityMine’s RealLifeApp and Web products. You will work with stakeholders across technical and non‑technical teams to scope requirements, optimise performance, and ensure our systems scale to handle Big Data. This is a hands‑on role that requires strong engineering practices, creative problem solving, and analytical thinking.

You will take full ownership of projects, including discovering and defining problems, cleaning and preparing data in the warehouse, developing and testing models, and deploying solutions into production environments.

Our offices are in Trafford Park, Manchester and the role consists of hybrid working, where we ask our team to be in the office for collaboration and team building 2 days per week. The rest of the week is up to you; deep focus at home, or more of the same!

Key Responsibilities:

• Build, maintain, and productionise machine learning models using PyTorch or similar frameworks.
• Design and optimise data pipelines for ML inference at scale.
• Work with large datasets using Big Data tools.
• Deploy ML workflows using AWS infrastructure.
• Collaborate with data engineers and product teams to integrate ML solutions into RealityMine’s products.
• Investigate and troubleshoot customer feedback on data quality and drive model improvements from experimentation.
• Promote best practices in ML engineering and data quality across the business.
• Adhere to Company Policies and Procedures with respect to Security, Quality and Health & Safety.
• AI first mindset to improve our products and tools within the business.

About You:

Here’s what we’re looking for:

• Experience: 2–3 years of production experience in machine learning systems.
• Proficiency in Python and SQL for analysis, model development, and data interrogation.
• Strong knowledge of PyTorch or similar ML frameworks.
• Experience handling large datasets and distributed processing with PySpark or similar is desirable.
• Experience of experimentation tools such as MLflow is a bonus.
• Comfort with deploying ML models into production environments.
• Familiarity with AWS or similar cloud vendor.
• A methodical, problem‑solving mindset with high attention to detail.
• Ability to scope, define, and deliver complex solutions independently.
• Self‑motivated, accountable, and keen to continuously learn and grow.
• Experience using AI tools to enhance productivity and quality.

Why Join RealityMine?

At RealityMine, we believe our people are at the heart of everything we do. That’s why we go the extra mile to support every team member to unlock their full potential. Whether you're hungry for learning, driven by achievement, or just love being part of a dynamic and supportive team, you'll find a home here.

Your Benefits

• Generous Time Off: Enjoy 25 days of paid holiday, plus bank holidays. After two years with us, you can also buy or sell up to 5 days of annual leave.
• Peace of Mind: Life assurance and a workplace pension with employer contributions.
• Reward for Performance: Bonus scheme that recognizes your hard work and contributions.
• Cycle to Work Scheme: For the cyclists among us, we've got you covered.
• Gear You’ll Love: Choose the tech that works for you, we'll try and source it!
• Learning & Growth: Benefit from one‑to‑one coaching, a budget for training programs, and all the support you need to keep growing.
• Giving Back: Join us in supporting local charities and making a positive impact.

Hybrid Working

We know work‑life balance matters, so we’ve embraced a flexible hybrid working model:

• Located in Trafford Park, our Manchester office offers an inspiring, collaborative space to work alongside your colleagues.
• Free parking and secure bike shed. Excellent public transport links.
• Split your time between the office and home, with 2 days working in our offices.
• Full equipment provided for home working (desk, screen, chair).
• Receive £100 annually to personalise your home workspace.
• Flexible start and finish times to suit your personal circumstances.

If you’re a Machine Learning Engineer professional excited to work on impactful projects and shape the future of data insights, we’d love to hear from you.

Please email your CV with the heading Machine Learning Engineer to [e-mail]