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- Tasks: Lead and manage the delivery of cutting-edge Machine Learning and AI platforms.
- Company: Join a forward-thinking tech 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 significant impact on global business.
- Qualifications: 8+ years in ML/AI with proven leadership and technical expertise.
- Other info: Dynamic team 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 employer: ON RUNNING
Contact Detail:
ON RUNNING Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineering Manager
✨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, it’s all about who you know!
✨Tip Number 2
Showcase your expertise! Create a portfolio that highlights your projects, especially those involving MLOps and AgentOps. Share your insights on platforms like LinkedIn or GitHub to demonstrate your knowledge and passion for the field.
✨Tip Number 3
Prepare for interviews by brushing up on technical concepts and leadership scenarios. Be ready to discuss how you've led teams and tackled challenges in ML projects. Practice makes perfect, so consider mock interviews with friends or mentors.
✨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 experience in building scalable ML systems and your leadership skills. Let’s build the future of AI together!
We think you need these skills to ace Machine Learning Engineering Manager
Some tips for your application 🫡
Showcase 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 those details!
Demonstrate Leadership Skills: Since this role involves managing teams, it’s crucial to showcase your proven people leadership experience. Share examples of how you've empowered your team and navigated trade-offs in delivering high-quality code.
Be Clear and Concise: When writing your application, clarity is key! Use straightforward language to convey your technical knowledge and experience. We appreciate a well-structured application that gets straight to the point.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy!
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 that showcase your experience in managing teams. Talk about how you've empowered your team members to deliver high-quality work and how you’ve navigated challenges in a collaborative environment.
✨Know Your Cloud Platforms
Familiarise yourself with cloud technologies, especially GCP, and be prepared to discuss your hands-on experience with automated CI/CD processes for ML. This will show that you’re not just a theoretical expert but also practical in your approach.
✨Communicate Effectively
Practice explaining complex technical concepts in simple terms. As a Machine Learning Engineering Manager, you’ll need to convey ideas clearly to diverse audiences, so think about how you can make your communication engaging and accessible.
