About Keyloop:
Keyloop bridges the gap between dealers, manufacturers, technology suppliers, and car buyers. We empower car dealers and manufacturers to fully embrace digital transformation by creating innovative technology that makes selling cars better for our customers, and buying and owning cars better for theirs. We use cutting-edge technology to link our clients’ systems, departments, and sites, providing an open technology platform that’s shaping the industry for the future. We use data to help clients become more efficient, increase profitability, and give more customers an amazing experience.
The Role:
We are hiring a Senior AI Engineer to join our growing AI Centre of Excellence. This is a hands-on technical role that spans Generative AI (GenAI), traditional Machine Learning (ML), and early-stage Data Science. You’ll play a critical part in delivering high-impact AI solutions, establishing best practices, and supporting the development of our AI capabilities across the business. You will work across the full AI lifecycle - from prototype to production - and contribute to platform development, MLOps/LLMOps infrastructure, and applied data science. This is a greenfield opportunity to have a direct impact on the direction of AI within Keyloop.
Key Responsibilities:
GenAI Development:
- Design, prototype, and build GenAI applications (e.g., co-pilots, retrieval-augmented generation, automation agents).
- Implement prompt engineering patterns, fine-tuning workflows, and LLM evaluation techniques.
- Stay up to date with advancements in foundation models and integration methods.
Machine Learning Engineering:
- Collaborate on the development, deployment, and monitoring of ML models.
- Contribute to experimentation design, data pipelines, and MLOps frameworks.
- Write production-grade code and support infrastructure for scalable model delivery.
Applied Data Science:
- Apply statistical techniques and modelling to support business decision-making.
- Develop metrics, A/B test frameworks, and causal inference pipelines.
- Support product teams with analytical insights and model-based features.
Engineering Practice:
- Participate in architecture reviews, code reviews, and technical design discussions.
- Contribute to reusable tools, components, and platform capabilities.
- Mentor junior engineers or data scientists where relevant.
Required Qualifications:
- Proven experience developing and deploying GenAI solutions (LLMs, RAG, agents).
- Strong Python skills and practical knowledge of LLM tooling (LangChain, Transformers, etc.).
- Experience with traditional ML workflows, from feature engineering to deployment.
- Exposure to MLOps/LLMOps practices (e.g., CI/CD for ML, monitoring, model registry).
- Familiarity with statistical methods and experimentation (A/B tests, uplift modelling).
- Working knowledge of cloud-native infrastructure (AWS preferred).
- Ability to write clean, production-grade code and collaborate with engineers and product managers.
Preferred Qualifications:
- Experience with AWS AI services (e.g., Bedrock, SageMaker, Lambda, Step Functions).
- Familiarity with low-code/no-code GenAI platforms.
- Exposure to platform engineering, API development, or DevOps for ML/AI systems.
- Interest in ethical AI, fairness, and governance practices.
Location:
UK (Reading); Poland; Italy; Spain (Homeworking); Finland (Homeworking); Czech (Prague)
Work Type:
Remote
