AI Engineer

• Design, build, and deploy Generative AI models for enterprise manufacturing and operational intelligence use cases.
• Develop and maintain end to end machine learning pipelines using modern MLOps frameworks including CI and CD, observability, automated testing, and monitoring.
• Work with large scale, multi region data sets including structured and unstructured data.
• Use tools such as Hugging Face, OpenAI, vector databases, and large language model frameworks to create advanced AI solutions.
• Optimise models through fine tuning, parameterisation, prompt engineering, and performance testing.
• Develop solutions across cloud environments including AWS, Azure, or GCP.
• Collaborate with engineering, platform, and enterprise architecture teams to embed AI into a core strategic platform.
• Maintain documentation, governance, testing standards, and responsible AI practice., * The opportunity to shape AI capability within a global manufacturing enterprise undergoing significant digital transformation.
• Collaboration with platform engineers, architects, and data teams building a flagship enterprise platform.
• Access to cutting edge AI tooling, cloud infrastructure, and research.
• Clear progression into senior or architecture level AI positions.

Experience Required: 3 years delivering live AI products and 5 years or more of theory and applied machine learning understanding

167 Solutions is supporting a world leading manufacturing organisation in the search for an experienced and ambitious AI Engineer specialising in Generative AI. This role is part of a major digital transformation programme and will contribute directly to an enterprise architecture platform used across global operations.

If you are passionate about building real AI systems that are used at scale, this opportunity offers genuine impact and long term progression., * A minimum of 3 years experience delivering live, production grade AI or machine learning systems.

• A minimum of 5 years theoretical understanding of machine learning, deep learning, NLP, and large language models.
• Strong experience with transformer models, embeddings, vector search, and Generative AI architectures.
• Practical experience using Hugging Face, OpenAI, LangChain, Retrieval Augmented Generation, and diffusion models.
• Strong MLOps experience including MLflow, Kubeflow, Airflow, Docker, Kubernetes, and CI and CD tooling.
• Strong programming skills in Python. Bash, SQL, and JavaScript are desirable.
• Proven experience working with large, complex, multi source data sets.
• Experience with consumer behavioural or market data is desirable.
• Comfortable working within agile engineering teams and enterprise environments.

Desirable Skills

• Experience with vector databases such as FAISS, Pinecone, or Weaviate.
• Knowledge of enterprise scale Retrieval Augmented Generation systems.
• Experience within global manufacturing, engineering, or industrial environments.
• Understanding of data governance, security, and responsible AI principles.