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For Companies At a Glance
- Tasks: Lead a team in developing cutting-edge AI solutions and mentor aspiring engineers.
- Company: Join Stratasys, a leader in 3D printing innovation with a collaborative culture.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make a real impact in AI while working with the latest technologies.
- Qualifications: 5+ years in ML/AI engineering and strong Python skills required.
- Other info: Dynamic environment with excellent career advancement opportunities.
The predicted salary is between 43200 - 72000 £ per year.
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.
Responsibilities
- 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.
Software Team Lead, AI in Cambridge employer: Stratasys Ltd
Contact Detail:
Stratasys Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Team Lead, AI in Cambridge
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and software engineering space. Attend meetups, webinars, or conferences where you can chat with industry folks. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI/ML. Whether it's GitHub repos or a personal website, let your work speak for itself. This is your chance to shine and demonstrate your hands-on development experience.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and leadership questions. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders. Mock interviews can be super helpful!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience in leading AI projects and mentoring others, and let’s get the conversation started!
We think you need these skills to ace Software Team Lead, AI in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your leadership experience in AI/ML and any hands-on development you've done. We want to see how you can lead a team while still getting your hands dirty!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you the perfect fit for this role. Don’t forget to mention specific projects or achievements that showcase your expertise.
Showcase Your Technical Skills: Since this role involves a lot of technical work, be sure to list your proficiency in Python and any ML frameworks you’ve used. If you have experience with deployment tools like Docker or cloud platforms, make that clear. We love seeing practical examples of your work!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Stratasys Ltd
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical skills listed in the job description, especially Python and ML frameworks like PyTorch and TensorFlow. Brush up on your experience with deploying models to production using Docker or Kubernetes, as these are crucial for the role.
✨Showcase Your Leadership Skills
Prepare examples of how you've successfully led teams in the past. Think about specific projects where you mentored team members or coordinated efforts across different departments. This will demonstrate your ability to manage a hybrid team effectively.
✨Communicate Clearly and Confidently
Practice explaining complex technical concepts in simple terms. You’ll need to communicate with both technical and non-technical stakeholders, so being able to articulate your thoughts clearly is key. Consider doing mock interviews to refine this skill.
✨Prepare for Scenario-Based Questions
Expect questions that ask how you would handle specific challenges, such as optimising model performance or managing project timelines. Think through potential scenarios and how you would approach them, showcasing your problem-solving skills and strategic thinking.
