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- Tasks: Lead and manage the delivery of cutting-edge Machine Learning and AI platforms.
- Company: Join a forward-thinking company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Shape the future of AI and make a real impact on global business.
- Qualifications: 8+ years in ML/AI with proven leadership and technical expertise.
- Other info: Dynamic environment with a focus on collaboration and innovation.
The predicted salary is between 54000 - 84000 £ per year.
Your mission as a ML Engineering Manager is to lead and manage the end-to-end delivery of cutting-edge, production-grade Machine Learning and AI platforms. This role requires you to set the technical direction for your domain and champion MLOps best practices, ensuring a focus on scalable and reliable systems. While our foundation is built on traditional MLOps, we are rapidly expanding into Agentic Intelligence. You will play a pivotal role in evolving our infrastructure to support autonomous agents that can reason, use tools, and drive business impact. You will not just lead a team; you will build the backbone of AI at On, turning massive data streams into the competitive edge that powers our global growth.
You are a proven domain expert and leader ready to manage one or more engineering teams, accountable for technical delivery, quality, and hiring in the ML platform space. You should be able to demonstrate:
- Deep Domain Expertise: 8+ years of related experience or equivalent, with deep technical expertise in ML and AI production implementation and MLOps and AgentOps principles, including a strong track record in building and operating robust, end-to-end machine learning pipelines.
- Proven People Leadership: Proven experience in managing one or more teams with Individual Contributors (ICs) under direct management. You possess the ability to empower your team to ship high-quality code at pace, helping them navigate trade-offs between perfect and 'production-ready'.
- Cloud & Platform Fluency: Expert knowledge of technology concepts such as streaming, architecture and AI-components like model stores or feature stores, with hands-on experience on cloud platforms (GCP preferred) and automated CI/CD for ML.
- Collaborative Influence: You are an exceptional communicator and a genuine team player, adept at guiding team decisions, fostering consensus through professional influence, and effectively conveying complex technical information to diverse audiences.
Machine Learning Engineering Manager in London employer: ON RUNNING
Contact Detail:
ON RUNNING Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineering Manager in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the ML and AI space. Attend meetups, webinars, or conferences where you can chat with industry leaders and potential employers. Remember, sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to MLOps and AgentOps. Use platforms like GitHub to share your code and demonstrate your expertise in building robust machine learning pipelines.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and leadership skills. Be ready to discuss your experience managing teams and delivering high-quality ML solutions. Practice common interview questions and scenarios that highlight your problem-solving abilities.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your deep domain expertise and collaborative influence, and let us see how you can contribute to our mission.
We think you need these skills to ace Machine Learning Engineering Manager in London
Some tips for your application 🫡
Show Your Expertise: Make sure to highlight your deep domain expertise in ML and AI. We want to see your experience with production implementation and MLOps principles, so don’t hold back on showcasing your achievements!
Leadership Matters: Since this role involves managing teams, share examples of how you've empowered your team members. We love to see how you’ve helped them navigate challenges and deliver high-quality work at pace.
Tech Savvy is Key: Demonstrate your fluency with cloud platforms and technology concepts relevant to the role. Mention any hands-on experience you have with GCP or CI/CD for ML, as this will really catch our eye!
Be a Team Player: We value collaborative influence, so make sure to convey your communication skills. Share instances where you’ve guided team decisions and fostered consensus, as this shows you’re not just a leader but also a great teammate.
How to prepare for a job interview at ON RUNNING
✨Showcase Your Technical Expertise
Make sure to brush up on your knowledge of MLOps and AgentOps principles. Be ready to discuss your past experiences in building and operating machine learning pipelines, as well as any specific projects that highlight your technical skills.
✨Demonstrate Leadership Skills
Prepare examples of how you've successfully managed teams in the past. Think about situations where you empowered your team to deliver high-quality work and navigated trade-offs effectively. This will show your potential employer that you can lead and inspire others.
✨Familiarise Yourself with Cloud Platforms
Since cloud fluency is key for this role, ensure you're up to speed with GCP and other relevant technologies. Be prepared to discuss your hands-on experience with automated CI/CD processes for ML, as this will be crucial in demonstrating your fit for the position.
✨Communicate Clearly and Collaboratively
Practice explaining complex technical concepts in simple terms. This will help you convey your ideas effectively during the interview. Remember, being a team player and showing your ability to foster consensus will be highly valued by the hiring team.