Company Description
Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services.
Job Description
We are seeking a hands‑on AI/ML Engineer to build, deploy, and optimise machine learning and generative AI solutions. The role focuses on developing production‑grade AI applications, integrating AI models into business systems, and supporting the full AI development lifecycle. The ideal candidate is passionate about modern AI technologies, software engineering best practices, and delivering reliable AI solutions at scale.
Key Responsibilities
AI Application Development
- Design, build, and maintain AI‑powered applications and services.
- Develop and deploy machine learning and generative AI solutions.
- Build Retrieval‑Augmented Generation (RAG) systems and AI agents.
- Integrate foundation models and APIs into enterprise applications.
- Create reusable AI components and frameworks.
Machine Learning Engineering
- Train, fine‑tune, evaluate, and deploy ML models.
- Develop feature engineering and model evaluation pipelines.
- Implement model monitoring and performance tracking.
- Optimize model inference performance and cost efficiency.
Generative AI Engineering
- Develop LLM‑based applications and workflows.
- Build prompt templates, agent frameworks, and orchestration pipelines.
- Implement vector search and knowledge retrieval systems.
- Design evaluation frameworks for AI quality, safety and reliability.
- Improve hallucination mitigation and response accuracy.
MLOps & Deployment
- Design and automate ML model training, validation and retraining pipelines.
- Version and manage datasets, features and model artefacts using tools such as MLflow or similar.
- Deploy and serve ML models via REST APIs or batch inference at scale on Databricks, Snowflake or similar.
- Monitor model performance in production, detecting drift and degradation.
- Manage feature stores and ensure data pipeline reliability for ML workloads.
- Implement experiment tracking and reproducibility across the model lifecycle.
Collaboration
- Work closely with Solution Architects, Product Managers and Engineering Teams.
- Participate in code reviews and technical design discussions.
- Support testing, deployment and ongoing optimisation activities.
Qualifications
Programming & Engineering
- Strong proficiency in Python and SQL.
AI & Machine Learning
- Experience with Scikit‑learn, PyTorch and/or TensorFlow.
- Experience with Hugging Face.
- Experience with main AI services from leading cloud service and model providers.
- Experience with supervised and unsupervised learning.
- Experience with model evaluation.
- Experience with feature engineering.
- Experience with statistical concepts.
Generative AI
- Practical experience building RAG systems, AI agents and LLM‑powered applications.
- Practical experience building vector search solutions.
- Familiarity with LangChain, LlamaIndex, Semantic Kernel and LangGraph.
Cloud & Infrastructure
- Experience with AWS, Azure or GCP.
- Experience with Docker and containerization.
- Experience with Kubernetes (preferred).
- Experience with CI/CD pipelines and DevOps practices.
Professional Experience
- 3+ years in ML engineering or data science, with demonstrable experience deploying models to production and building Gen AI applications including RAG systems, LLM integration or agentic workflows.
- Demonstrated experience delivering AI solutions into production environments.
Benefits
- Quarterly Performance‑Related Profit Share Scheme.
- Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme.
- Flexible/remote working.
- Financial Wellbeing initiatives including pension, private healthcare cover, life assurance, financial advice and employee discount scheme.
- Employee Wellbeing schemes including gym discounts, bike to work, fitness classes, mindfulness workshops, employee assistance programme and more, plus generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies.
- Educational assistance and incentivised certifications and accreditations, including AWS, Microsoft, Oracle and Red Hat.
- Reward schemes including Annual Excellence Awards & ‘Call‑Out’ platform.
- Environment, Social and Community First initiatives allowing involvement in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes.
Equal Opportunity and Diversity Commitment
Version 1 is an equal opportunities employer. We are committed to building a diverse, inclusive and respectful workplace where everyone feels valued and able to thrive. We welcome applications from people of all backgrounds, identities and lived experiences, and we value the different perspectives people bring.
