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Sundayy

ML Engineer

England
Posted about 15 hours ago
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About The Company

Just Eat Takeaway.com is a leading global online food delivery platform dedicated to empowering everyday convenience. Our mission is to connect millions of customers with a vast network of restaurants, grocery stores, and convenience partners across 14 countries through innovative technology. We strive to deliver seamless, reliable, and personalized experiences that make ordering food, groceries, and essentials simple and accessible. Our commitment to excellence and customer satisfaction has positioned us as a trusted name in the online delivery industry, fostering a dynamic and inclusive work environment where innovation and collaboration thrive.

About The Role

We are seeking a highly skilled and experienced Staff Machine Learning Engineer to join our AI Growth team. In this pivotal role, you will lead the development and evolution of our machine learning infrastructure, enabling the delivery of advanced AI capabilities across our marketplace. Your expertise will guide the architecture, roadmap, and engineering strategies that support our foundation model platform and generative AI initiatives. Collaborating closely with cross-functional teams including engineers, data scientists, and platform specialists, you will ensure our ML systems are scalable, reliable, and aligned with our business objectives. This role offers an exciting opportunity to shape the future of AI at scale, driving innovation and operational excellence in a fast-paced environment.

Qualifications

  • Proven experience in defining and executing technical roadmaps for large-scale machine learning platforms
  • Deep understanding of production ML architecture, including latency, model quality, and infrastructure cost management
  • Hands-on experience with deploying and managing Large Language Models (LLMs) and Generative AI solutions
  • Expertise in model serving architectures, including online, batch, synchronous, and asynchronous strategies
  • Strong knowledge of Kubernetes, cloud platforms (GCP, AWS), and distributed ML workloads
  • Experience with monitoring ML models for performance, drift, and operational health
  • Excellent stakeholder management and cross-team collaboration skills
  • Pragmatic problem-solving approach with a focus on scalable, maintainable solutions
  • Ability to optimize GPU infrastructure and cloud resources for efficiency and cost reduction
  • Mentoring skills and a passion for fostering a collaborative engineering culture

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Responsibilities

  • Own and define the technical roadmap for the ML infrastructure domain, including GPU compute, model serving, and observability
  • Lead the development of our foundation model platform, expanding from a GCP-first environment to a hybrid AWS and GCP architecture
  • Establish and implement GPU compute strategies across Kubernetes, Vertex AI, and SageMaker, balancing performance and cost
  • Drive the adoption of Generative AI and LLM capabilities, establishing best practices for evaluation, deployment, and governance
  • Collaborate with engineering teams to resolve dependencies and technical blockers impacting delivery
  • Provide architectural guidance and technical leadership across multiple teams and projects
  • Partner with product, platform, and infrastructure teams to ensure ML systems are scalable, reliable, and aligned with business goals
  • Enhance platform observability by monitoring model performance, training efficiency, and operational health
  • Mentor engineers, promote engineering excellence, and facilitate knowledge sharing
  • Make strategic architectural decisions that support long-term growth and platform sustainability

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Benefits

  • Competitive salary and performance-based bonuses
  • Comprehensive health insurance coverage
  • Flexible working hours and remote work options
  • Opportunities for professional development and continuous learning
  • Inclusive and diverse work environment that fosters innovation
  • Participation in cutting-edge AI projects impacting millions of users worldwide
  • Collaborative culture that values growth, movement, and celebrating achievements

Equal Opportunity

Just Eat Takeaway.com is committed to creating an inclusive environment where all employees feel valued and respected. We are an equal opportunity employer and do not discriminate based on race, ethnicity, gender, age, sexual orientation, disability, or any other protected characteristic. We believe diversity drives innovation and excellence, and we welcome applicants from all backgrounds to join our team and contribute to our shared success.

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Skills

Machine Learning Infrastructure
Large Language Models
Generative AI
Kubernetes
Google Cloud Platform
Amazon Web Services
Model Serving
GPU Optimization
Vertex AI
SageMaker
ML Observability
Technical Roadmap Execution
Distributed ML Workloads
Stakeholder Management
Architectural Design
Mentoring

Location

England, United Kingdom

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