Research jobs in United Kingdom

Location: Cambridge, UK

We are seeking a hands‑on AI Team Lead to guide a team of machine‑learning and software engineers while actively contributing to model development, architecture, and production deployment. This role combines technical leadership, project management, and practical coding in a fast‑paced environment.

• Lead end‑to‑end development of AI/ML solutions, from research and prototype to production.
• Define technical direction, architecture, and best practices for AI models, data pipelines, and infrastructure.
• Review code and ML pipelines to ensure high quality, scalability, and reliability.
• Mentor, coach, and develop team members.

• Build, train, fine‑tune, and evaluate machine‑learning models (NLP, CV, tabular, generative AI, etc.).
• Develop production‑ready code in Python or other relevant languages.
• Implement model monitoring, performance optimization, and CI/CD automation for ML systems.

• Translate business requirements into technical AI solutions and delivery plans.
• Coordinate sprint planning, workload distribution, and roadmap execution.
• Collaborate with product, data, and engineering teams to deliver high‑impact AI features.
• Communicate technical choices, risks, and results to leadership and non‑technical stakeholders.

• 5+ years experience in ML/AI engineering, plus 1–3 years in a leadership or senior role.
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit‑Learn).
• Experience deploying models to production (Docker, Kubernetes, AWS/GCP/Azure).
• Solid understanding of LLMs, embeddings, vector search, RAG pipelines, or generative AI.
• Experience with MLOps tools (MLflow, SageMaker, Vertex AI, Databricks, etc.).
• Strong communication, leadership, and project execution skills.

• Experience managing a hybrid team: data scientists, ML engineers, and software engineers.
• Background in reinforcement learning, optimization, or computer vision.
• Experience with LangChain/LlamaIndex or similar orchestration frameworks.
• Familiarity with data engineering tools (Airflow, dbt, Snowflake, Kafka).
• Prior startup or rapid‑growth environment experience.

• Delivering production‑ready AI systems that impact business KPIs.
• Growing and leveling‑up team capabilities.
• Building reliable, scalable AI infrastructure and model lifecycle processes.
• Leading cross‑functional initiatives that bring new AI features to market.

Stratasys, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to their protected Veteran or disabled status and will not be discriminated against for their race, color, religion, sex, age, disability, military status, or national origin or any other characteristic.