Gravitas Recruitment Group (Global) Ltd
AI / Machine Learning Engineer
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£70,000
Our client is a specialist AI consultancy delivering innovative Machine Learning and Generative AI solutions for a range of organisations. They work across the full AI lifecycle, helping clients successfully move from concept and experimentation through to production deployment.
Joining a highly collaborative team of AI specialists, you'll have the opportunity to work on technically challenging projects whilst learning from experienced practitioners who value knowledge sharing, continuous improvement, and collective success.
The Opportunity
This is an exciting opportunity for an AI / Machine Learning Engineer who is passionate about both technology and teamwork.
Working closely with senior engineers and technical leadership, you'll contribute to the design, development, and deployment of AI solutions that deliver measurable business value. You'll be given ownership and responsibility from day one, whilst benefiting from mentorship, collaboration, and exposure to a broad range of technologies and client challenges.
The successful candidate will enjoy working as part of a close-knit team, actively contributing ideas, sharing knowledge, and continuously developing their technical and commercial understanding of AI.
Responsibilities
- Design, develop, and deploy machine learning and AI solutions across a variety of client projects.
- Contribute to the full machine learning lifecycle, from research and prototyping through to production deployment and optimisation.
- Build applications leveraging Generative AI, Large Language Models (LLMs), and traditional machine learning techniques.
- Develop scalable backend services and production-ready ML pipelines.
- Work closely with colleagues and stakeholders to understand requirements and translate them into effective technical solutions.
- Clearly communicate technical concepts, decisions, and outcomes to both technical and non-technical audiences.
- Participate in technical discussions, knowledge-sharing sessions, and collaborative problem-solving activities.
- Stay current with developments in AI and contribute new ideas to the team.
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What We're Looking For
- 2-6 years' experience in Machine Learning, AI Engineering, Data Science, or a related field.
- Hands-on experience developing and deploying machine learning models in production environments.
- Exposure to Generative AI, LLMs, RAG architectures, or adjacent AI technologies.
- Strong Python and software engineering fundamentals.
- Experience working with cloud platforms such as Azure, AWS, or GCP.
- A solid understanding of the end-to-end ML lifecycle.
- Strong problem-solving and analytical skills.
Equally Important
We're looking for someone who:
- Enjoys working closely with others and contributing to a collaborative team environment.
- Is excited by the opportunity to learn from experienced engineers and continuously develop their skills.
- Can effectively communicate their work, thought process, and technical decisions.
- Takes ownership whilst remaining open to feedback and new perspectives.
- Brings enthusiasm, curiosity, and a genuine interest in solving real-world problems with AI.
- Values team success as highly as individual achievement.
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Desirable Experience
- MLOps tooling and deployment frameworks.
- Docker, Kubernetes, and cloud-native architectures.
- Client-facing, consultancy, or stakeholder engagement experience.
- Strong academic background in Computer Science, Mathematics, Statistics, Engineering, or a related discipline.
What's on Offer
- The opportunity to work on cutting-edge AI and Generative AI initiatives.
- Exposure to the latest technologies and evolving AI landscape.
- A highly ambitious, collaborative, and supportive technical team.
- Significant scope for professional development and career progression.
- A culture that values curiosity, initiative, teamwork, and continuous learning.
Applicants must have the right to work in the UK.
If you're an AI Engineer who enjoys building innovative solutions, learning from talented colleagues, and contributing to a team-first environment, we'd love to hear from you.
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