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- Tasks: Assist in designing and developing machine learning processes for various clients.
- Company: Data Reply is a leading data specialist offering innovative AI and ML solutions.
- Benefits: Enjoy extensive training, hackathons, and a vibrant work environment with peers who share your passion.
- Why this job: Work on exciting projects with top brands while growing your skills in a supportive culture.
- Qualifications: A minimum 2.1 degree in Engineering/Computer Science; experience in ML model deployment preferred.
- Other info: Flexible travel opportunities and a commitment to diversity in the workplace.
The predicted salary is between 28800 - 48000 £ per year.
Career Opportunities: Graduate AI and Machine Learning Engineer (10980)
Requisition ID10980-Posted – Years of Experience (2) –Technology– Where (1) –Job
Graduate AI and Machine Learning Engineer
About Threepipe Reply:
Threepipe Reply is an award-winning integrated brand performance agency of specialists, working across; media, creative, social, analytics, UX, data science, search marketing and PR. Threepipe offers a rigorous planning framework, proprietary and best in breed technology partners to help consumer and business to business brands make sense of the highly evolving market, media and competitor landscape.
Role overview:
As a Graduate AI and ML Engineer, you’ll support the design and build and operational maintenance of applied AI and data engineering solutions that make a real impact across the agency. You’ll work on everything from improving and maintaining our internal systems and data pipelines, to developing AI-powered applications and prototypes for client work. This is a unique opportunity to join at the start of our tech journey and help shape how AI and advanced data engineering transforms our agency. You\’ll also assist our team in the design and development of machine learning processes in a variety of client environments. You will support the analysis of client requirements and help generate suitable recommendations. You will help manage the ML lifecycle from data selection and collection, ML model design and creation all the way through to operationalisation and monitoring. Start date: February 2026
Responsibilities:
- Developing new applications to support marketing performance and automation
- Build AI-powered prototypes and applications using LLMs, LangChain, RAG pipelines, and other emerging frameworks.
- Experiment with new AI technologies (e.g. vector databases, embedding models, prompt optimisation, AI agent, Google AI Studio/Gemini) and assess their value to the agency.
- Managing and improving our cloud infrastructure structure and data pipelines; help deploy and manage containerised services.
- Working with our Data Analysts and data team members to better improve our data infrastructure, transformations and reporting flows.
- Support the management of infrastructure and orchestration pipelines needed to automatically train and bring machine learning models to production
- Explore and understand client data in relation to the problem you’re tackling and communicate findings to clients and stakeholders
- Collaborate with non-technical teams to understand business problems and turn them into AI and data solutions.
- Responsible for supporting, managing and maintaining our internal website and applications, including assisting with future migration/modernisation and working with external partners where required
About the candidate:
- Degree-educated in Computer Science, Artificial Intelligence, Data Science, or in a related discipline (min 2.1 grade)
- Initial work experience working in relevant role (e.g. data engineering, developing AI solutions, training, evaluating or deploying machine learning models)
- Practical experience with at least one major cloud platform (GCP or AWS) and working knowledge of its database/compute services
- Experience with MySQL and confident SQL skills (e.g., PostgreSQL /BigQuery-style SQL)
- A successful history of manipulating, processing and extracting value from large, disconnected datasets.
- Excellent knowledge of Python and data handing libraries (Python3 and specifically Pandas) including at least one ML framework e.g. Pytorch, Tensorflow and SKLearn as well as initial knowledge of LangChain and RAG.
- Familiarity with DevOps, Git/Github and CI/CD workflows is required and experience with containerisation and deployment using Docker/Kubernetes will be considered a plus
- Comfortable working with REST APIs and integrating platform exports into reporting pipelines
- Experience with Looker Studio, Funnel.io, Supabase, Bolt or similar tools is advantageous
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GRADUATE AI AND MACHINE LEARNING ENGINEER employer: Reply, Inc.
Contact Detail:
Reply, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GRADUATE AI AND MACHINE LEARNING ENGINEER
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning. Follow industry leaders on social media, read relevant blogs, and participate in online forums to stay updated. This knowledge will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Build a portfolio showcasing your projects related to machine learning and AI. Include any hackathons, code challenges, or personal projects that demonstrate your skills in Python, TensorFlow, or PyTorch. A strong portfolio can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the field by attending meetups, webinars, or conferences focused on AI and machine learning. Making connections can lead to valuable insights and potential job referrals, so don’t hesitate to reach out to others in the industry.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and understanding the machine learning lifecycle. Use platforms like LeetCode or HackerRank to sharpen your skills, and be ready to discuss your approach to problem-solving during the interview.
We think you need these skills to ace GRADUATE AI AND MACHINE LEARNING ENGINEER
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences related to AI and machine learning. Emphasise your knowledge of Python, machine learning frameworks like PyTorch and TensorFlow, and any experience with AWS.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and machine learning. Mention specific projects or experiences that demonstrate your ability to work in a team and tackle complex problems.
Showcase Relevant Projects: If you have worked on any projects related to machine learning or data science, include them in your application. Describe your role, the technologies used, and the outcomes achieved to illustrate your hands-on experience.
Highlight Soft Skills: In addition to technical skills, emphasise your communication abilities and flexibility. Mention how you can articulate complex information clearly and your willingness to adapt to different client projects.
How to prepare for a job interview at Reply, Inc.
✨Showcase Your Technical Skills
Make sure to highlight your knowledge of Python, especially libraries like PyTorch, TensorFlow, and Scikit-learn. Be prepared to discuss any projects or experiences where you've applied these skills, as well as your understanding of CI/CD workflows and containerisation.
✨Demonstrate Your Problem-Solving Ability
Prepare to discuss specific challenges you've faced in previous roles or projects related to machine learning. Explain how you approached these problems, the solutions you implemented, and the outcomes. This will show your analytical thinking and ability to tackle complex issues.
✨Communicate Effectively
Since excellent communication skills are essential for this role, practice articulating complex technical concepts in a clear and concise manner. Think about how you would explain your work to someone without a technical background, as you'll need to communicate findings to clients and stakeholders.
✨Emphasise Your Growth Mindset
Be ready to discuss how you've embraced new challenges in your career. Share examples of how you've learned from past experiences and adapted to new technologies or methodologies. This will demonstrate your willingness to grow and evolve in the fast-paced field of AI and machine learning.
