Senior Machine Learning Engineer, Growth

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About the role

We are seeking a Senior Machine Learning Engineer to join the Growth Tech Alliance. In this role, you will architect and deploy the robust infrastructure behind our intelligent marketing systems. You will be responsible for maturing algorithmic prototypes into high-performance production systems, ensuring our AI-driven marketing optimization is served reliably and autonomously at a global scale. S'more about the team We are hiring a Senior Machine Learning Engineer to take our AI tooling to the next level by architecting and deploying the robust infrastructure behind our intelligent marketing optimization systems. You will provide critical engineering execution for our AI initiatives. You will develop scalable microservices for predictive scoring, orchestrate complex LLM-based agents for creative intelligence. As the ML engineering expert for the team, you will drive the maturation of algorithmic prototypes into high-performance production systems with maximum Speed & Agility, shaping the future of how HelloFresh automates marketing at an unprecedented scale. Lettuce share what this role will be responsible for As a core member of the engineering team, you will focus on productionizing ML infrastructure across several domains: • Build robust integration layers for visual AI pipelines that process multi-modal embeddings that power various predictive models. • Transition proof-of-concept models into resilient production microservices and architect LLM-based orchestration frameworks. • Engineer high-throughput, low-latency data pipelines to process 1P data and pipeline signals into external platforms like Meta and Google. • Collaborate with data scientists and other engineers in a cross-functional team to improve HelloFresh’s value forecasting efficiency. • Establish CI/CD processes, feature stores, and drift detection to ensure continuous delivery and model reliability. • Work beyond your specialization when the problem demands it. Your specialization is your anchor, not your boundary. • Operate what you build. You instrument, monitor, and improve your systems in production. Shipping is the beginning of the learning cycle, not the end. • All other duties, as assigned Sound a-peeling? Here's what we're looking for • Hands-on experience working with AI tooling (e.g., Claude Code, Cursor, Copilot) beyond casual experimentation. You use AI agents every day. You have a practical sense of how the context you provide to AI tools shapes output quality, and how to set boundaries on AI-generated work. • Experience leading the end-to-end lifecycle of production ML systems, from architectural design to scalable deployment and monitoring. • Expertise in leveraging hyperscaler ecosystems (AWS, GCP, Azure) to build cost-effective, resilient, and automated ML infrastructure. • Deep technical proficiency with modern ML frameworks (PyTorch, TensorFlow, HuggingFace) • Expert programming skills in Python and PySpark. • A BS/MS in Computer Science or a related engineering field, coupled with a proven track record of bringing ML systems from prototype to high-traffic production. • Proven experience engineering robust data architectures that reliably process and combine diverse data formats, ranging from structured offline conversion data to unstructured multimedia assets. • A demonstrated bias for action and extreme ownership, eager to adopt Gen AI tools to creatively solve architectural challenges and enhance engineering velocity. • You take full ownership. You have a bias to ship. You finish the last twenty percent. • You have product sense and are opinionated about what should be built and why, and you can back that opinion with data and user evidence. Let’s cut to the cheese, this is why you'll love it here • Box Discount - A

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