Software Team Lead, AI

Stratasys is a world leader in 3D printing!

LOCATION: Cambridge, UK Hybrid- 3 days in office

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.

Responsibilities:

Technical Leadership

• 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.

Hands-On Development

• 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.

Project & Stakeholder Management

• 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

Required Skills

• 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.

Nice to Have

• 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

What Success Looks Like

• 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.