Machine Learning Engineering Manager
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Job Summary
Machine Learning Engineering Manager
Join us in our mission to transform the way people shop and eat where impact innovation and growth drive everything we do. At Deliveroo machine learning is the heartbeat of our three-sided marketplaceconnecting millions of consumers riders and partners in real-time. We are looking for a leader to own the algorithmic systems that ensure our delivery network remains the most efficient in the world.
As a Machine Learning Engineering Manager you will lead teams focused on Delivery Logistics and Consumer Signals. You will sit at the high-stakes intersection of real-world physics and real-time computation directly impacting food quality delivery speed and customer trust.
What Youll Be Doing
You will lead cross-functional teams of approximately 9 individual contributors (Machine Learning Engineers and Data Scientists) overseeing the systems that power the moment of truth in delivery.
Handover Logistics: Build and scale models that optimize rider dispatch based on food preparation times ensuring riders arrive exactly when the food is ready so orders arrive hot and fresh.
Consumer Signals: Own the ML systems that communicate network status to consumers including highly accurate delivery time estimates (ETAs) and dynamic restaurant availability.
Marketplace Balance: Take responsibility for core delivery performance metrics managing surge requirements network balance and real-time restaurant ranking adjustments.
Production Excellence: Translate complex noisy real-world delivery problems into production-grade ML and optimization systems.
Cross-Functional Partnership: Partner with Product Managers Software Engineers and Operations teams from initial problem framing through to global deployment and iteration.
Team Development: Lead and develop your teams technical and career growth fostering a culture of experimentation and technical quality.
What Youll Need to Thrive
We are looking for a pragmatic impact-focused leader who understands that in logistics done is often better than theoretically perfect.
People Leadership: Experience line managing MLEs and Data Scientists with a track record of supporting career development.
Technical Depth: Hands-on experience building and deploying ML or optimization systems into production at scale.
Domain Expertise: A strong background in logistics supply chain network optimization or consumer-facing real-time systems.
Pragmatism: Comfort operating in fast-changing environments with noisy data and the ability to make difficult technical trade-offs.
Collaborative Mindset: Experience working within Product Squads alongside engineers and operational stakeholders.
Why Join Us
At Deliveroo youll work on machine learning systems that operate in real-time at global scale shaping the movement of millions of orders every day.
Measurable Impact: Own business-critical systems where improvements directly translate to faster deliveries and happier customers.
Growth & Community: Be part of a supportive world-class ML and Data Science community with ample opportunities for technical and managerial growth.
Real-World Challenges: Solve some of the most interesting last-mile logistics problems in the tech industry today.
Diversity Equity and Inclusion
At Deliveroo we believe a great workplace reflects the world around us. We are committed to building a team that represents a variety of backgrounds perspectives and skills.
Our 2024 Global Workforce Diversity data highlights our ongoing commitment to representation:
Ethnic Diversity (UK Corporate): 38.2% of our employees identify as being from ethnic minority backgrounds. This includes:
19.4% Asian / Asian British
7.1% Black / African / Caribbean / Black British
5.8% Mixed / Multiple ethnic groups
5.9% Other ethnic groups
Gender Representation: 44.1% of our global corporate workforce identifies as women.
Senior Leadership: We are actively working toward a global goal of 40% women in senior leadership roles.
We welcome candidates from all backgrounds. If you require any reasonable adjustments during the recruitment process please let your recruiter know or contact us at
Required Experience:
Manager
Key Skills
- Hospitality Experience
- Go
- Management Experience
- React
- Redux
- Node.js
- AWS
- Mechanical Engineering
- Team Management
- Leadership Experience
- Mentoring
- Distributed Systems
