Graduate Machine Learning Engineer

Start Your Career as a Machine Learning Engineer

Are you excited by the idea of building intelligent systems that learn from data? Are you looking to start a career at the intersection of software engineering and data science?

We are looking for a motivated and curious Graduate Machine Learning Engineer to join our growing AI & Machine Learning team. In this role, you’ll help design, develop, and deploy machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists.

Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love to build, and eager to learn, this is the perfect opportunity to kickstart your career.

What You’ll Be Doing

You’ll play a key role in helping our team develop and deliver ML-powered solutions:

• Model Development: Assist in building and training machine learning and deep learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn
• Data Preparation: Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models
• Feature Engineering: Support the design and selection of relevant input features to improve model performance
• Model Evaluation: Learn to test models for accuracy, robustness, and fairness using best practices
• Deployment: Help package and deploy ML models into production using tools like Docker, APIs, or cloud platforms
• Collaboration: Work closely with software engineers, data scientists, and product teams to integrate ML into real products and services
• Experimentation: Participate in testing new algorithms, researching techniques, and iterating on models to improve performance

What We’re Looking For

We’re looking for graduates with strong technical foundations, problem-solving abilities, and a hunger to grow in the ML space.

Essential:

• A recent graduate (or soon-to-be) in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics, or a related discipline
• Proficiency in Python and familiarity with ML libraries such as Scikit-learn, TensorFlow, or PyTorch
• Strong understanding of basic machine learning concepts and algorithms (e.g. regression, classification, decision trees)
• Good grasp of data structures, algorithms, and programming fundamentals.
• Analytical mindset and strong problem-solving skills
• Excellent communication skills and a team-oriented attitude

Nice to Have (But Not Required):

• Internship, university project, or research involving machine learning or data science.
• Experience with cloud platforms (AWS, GCP, or Azure)
• Knowledge of software engineering best practices, version control (Git), or CI/CD pipelines
• Understanding of deep learning, NLP, or computer vision
• Familiarity with deployment tools like Docker or MLflow

What You’ll Gain

• Hands-on Experience: Work on real ML systems and contribute to production-grade solutions
• Mentorship & Training: Learn from senior ML engineers and participate in structured onboarding and learning paths
• Career Growth: Clear progression toward mid-level engineering or specialist roles in ML, NLP, or MLOps
• Innovation Culture: Be part of a forward-thinking team that values creativity, experimentation, and collaboration

Excellent Company Benefits

• 25+ Days Annual Leave + bank holidays
• Flexible / Hybrid Working Options
• Annual Bonus Scheme
• Support for Certifications and Training Courses (e.g., TensorFlow Developer, AWS ML Speciality)
• Private Medical & Mental Health Support
• Tech Budget – choose your own laptop, setup, and productivity tools
• Matched Pension Contributions
• Cycle-to-Work Scheme & Commuter Benefits
• Hackathons, Innovation Days, and Regular Team Events
• Employee Discounts & Perks