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Staff Machine Learning Engineer, AdTech
HelloFresh
Source: Headcount Labs · original listing ↗
Job data: Headcount Labs, ODbL 1.0. Job descriptions belong to their employers.
Posted today
About this role
S'more about the team The Growth Tech Alliance's goal is to enable HelloFresh to drive smarter marketing through AI-powered automation, intelligent systems, and advanced optimization. We've pioneered cutting-edge approaches to programmatic campaign optimization using state-of-the-art AI/ML technologies and are now scaling these capabilities across our global marketing operations. Our team’s key responsibilities include designing, building, maintaining autonomous decision-making systems, advanced ML models for marketing optimization, and real-time intelligence that drives measurable business impact. We work at the intersection of modern AI architectures, agentic systems, and enterprise-scale ML operations. We are looking for a Staff Machine Learning & AI Engineer to lead the engineering architecture of our multi-agent AI systems, with a focus on agent-driven products. In this role, you will bridge the gap between our data scientists and backend engineers, connecting internal automation APIs, AI agents, and the supporting ML models into a cohesive production platform. At HelloFresh, Staff Engineers are hands-on builders. You will spend roughly 50% of your time writing production code and building critical systems, and 50% driving technical direction through architecture reviews, RFCs, and mentoring engineers and data scientists across the team. Lettuce share what this role will be responsible for Design, build, and maintain production multi-agent AI systems and LLM workflows using modern orchestration frameworks such as LangChain and LangGraph. Build the APIs, tool-calling interfaces, and MCP integrations that connect our internal marketing automation services with AI agents and third-party platforms. Partner with Data Scientists to take machine learning and statistical models from prototype into reliable production, and connect them to the agents that create, launch, and optimize ads. Design end-to-end system architectures across our models, databases, and backend services, optimizing for reliability, correctness, and long-running workflows at scale. Build evaluation pipelines, guardrails, state management, and human-in-the-loop approval workflows to ensure AI and ML systems run safely in production. Author RFCs and Architecture Decision Records (ADRs) to align the team on technical direction and solve cross-team architectural challenges. Raise the engineering bar across the team through code reviews, system design guidance, and active mentorship of Senior Engineers and Data Scientists. All other duties, as assigned Sound a-peeling? Here's what we're looking for Extensive hands-on experience in Machine Learning Engineering, AI Engineering, or Backend Software Engineering, with a strong track record of building and operating distributed production systems. Production proficiency in Python and SQL, with strong fundamentals in software design, API development (e.g., FastAPI), testing, and database optimization. Hands-on experience building and deploying production LLM and agentic applications beyond simple prototypes, including agent orchestration (LangGraph/LangChain or similar ), tool use, MCP, context management, and automated evaluations. Experience with A/B testing or other experimentation methods (e.g., synthetic testing) to validate changes before and after launch. Experience with multi-agent systems (e.g., supervisor and sub-agent designs) and the ability to explain the trade-offs between single-agent and multi-agent approaches. Experience with multimodal AI models (vision-language models for image or video analysis and generation). Experience building systems where predictive ML models and LLM-based agents work together to drive automated decisions. Prior background in AdTech, MarTech, e-commerce growth, or high-scale consumer platforms. Familiarity with deploying and scaling classical machine learning or deep learning models in production, alongside solid MLOps practices (CI/CD, model monitoring, and automated pipelines). Experience working with modern cloud and data platforms such as Databricks, Unity Catalog, MLflow, Docker, and AWS. Proven experience operating at a Staff or Principal level—able to think in systems, navigate ambiguity, write clear technical specs, and mentor other engineers. Let’s cut to the cheese, this is why you'll love it here Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box. Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships! RRSP Matching - Competitive RRSP matching program offered Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. Family Benefits - A parental leave top-up program for expectant parents. Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun! Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts. Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names! Flexible Hybrid Approach At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week. #LI-HYBRID HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team. This is a posting for an existing vacancy. We are actively seeking to fill this position.