# Staff Machine Learning Engineer, AdTech at HelloFresh > Canada · Staff · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Ahellofresh%3A8265299 (read 2026-11-12). ## Facts (observed) - Company: [HelloFresh](https://alderhq.app/companies/hellofresh) - Location text: Toronto, Ontario, Canada; Toronto, ON, Canada - Where it can be done from (inferred): Canada (evidence: "Location: Toronto, Ontario, Canada; Toronto, ON, Canada") - Posted: 2026-11-11 (0 days ago) - First seen by alder: 2026-11-12 · last verified: 2026-11-12 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://careers.hellofresh.com/global/en/job/8265299?gh_jid=8265299 - Skills listed (inferred): Python, FastAPI, AWS, Docker, SQL, LLMs, Distributed systems ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Toronto, n 5): p25 CAD 198k, median CAD 200k, p75 CAD 202k - H-1B filings at this company for similar roles, FY26: 1 ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance)) ## Description (the employer's text) ### 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. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Ahellofresh%3A8265299 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.