Senior Staff Machine Learning Engineer - Menu Personalization

About HelloFresh

HelloFresh is transforming the way people eat by delivering high-quality food and recipes tailored to diverse meal occasions. Celebrating over a decade of growth, the company operates globally across 18 countries on three continents. Our meal kits, filled with exciting recipes and fresh ingredients, foster a community that seeks delicious, healthy, and sustainable choices. The HelloFresh Group includes multiple brands such as Green Chef, EveryPlate, Chefs Plate, Factor_, YouFoodz, The Pets Table, and GoodChop.

About the Team

The Menu Personalization team controls the recommender systems influencing what millions of customers see weekly when accessing HelloFresh. This group incorporates Data Scientists, Backend Engineers, Data Engineers, ML Engineers, and Product professionals who collaborate to move ideas from experimentation to production. Their work enhances customer experiences and business growth by improving how quickly customers find recipes they love, reinforcing HelloFresh as a weekly staple.

Role Overview

We seek a technical leader to oversee the Menu Personalization machine learning systems, owning the recommender technology stack in production. This role includes setting strategic direction for system design, development, and operations covering feature pipelines, training workflows, model deployment, experimentation tooling, and underlying infrastructure. The decisions made here will shape our platform’s future for years ahead. You will collaborate closely with Data Scientists to operationalize models, Data Engineers on feature pipelines, Backend Engineers on inference pathways, and Product teams on future initiatives. Your impact will extend across HelloFresh by driving engineering standards, architectural choices, mentorship, and company-wide ML and data engineering advancements.

Key Responsibilities

• Define and lead the technical vision for the full ML system stack supporting menu personalization, including pipelines, workflows, model serving, experimentation, and infrastructure.
• Translate research outputs and experiments into scalable, reliable production services partnering with Data Scientists to meet latency, scalability, and observability requirements.
• Collaborate with Product and Engineering leadership to shape the personalization roadmap, advocating your data-backed perspectives.
• Maintain operational excellence by monitoring, diagnosing, and enhancing system performance in production.
• Elevate team competence via architecture guidance, mentorship, and exemplifying best practices in production ML engineering.
• Make forward-thinking architectural and platform decisions with impact spanning multiple years.
• Drive standards and engineering excellence beyond your team, influencing other ML and data groups and contributing to broader company initiatives.
• Coordinate with peers company-wide to share best practices and propel the maturity of ML and data engineering efforts.

Required Qualifications

• Over 8 years of experience building and supporting production machine learning systems with demonstrated leadership at scale.
• Proven history of architectural choices that endure over multiple years and positively affect cross-team collaboration.
• Strong experience with recommender systems or extensive personalization platforms is highly advantageous.
• Proficiency with the data and ML technology stack, including Python and Spark, alongside backend and platform tools like Go, Kafka, and Kubernetes. Deep hands-on experience with pipelines, model serving, and observability in large-scale environments.
• Solid statistical understanding for designing valid experiments and evaluating model performance critically.
• Sound operational insights to diagnose system issues and create debuggable, efficient production solutions.
• Daily practical use of AI software tools such as Claude Code, Cursor, and Copilot, with a keen understanding of how provided contexts affect AI outputs.
• Strong product orientation with the ability to form clear priorities, justify them with data, and translate them into business outcomes.
• An ownership mindset with a strong focus on delivering complete, high-quality results.

Benefits and Culture

• Generous discounts on weekly HelloFresh and partner meal kits (75%) and Factor meal boxes (50%).
• Comprehensive health and dental benefits from day one, including a Health Spending Account, unlimited Headspace app access, and reduced-price GoodLife fitness memberships.
• Flexible vacation and paid time off policies supporting work-life balance.
• Parental leave top-up programs for expectant parents.
• Continuous learning and career development support through dedicated teams and resources.
• Engagement in team activities and company-wide events promoting a fun and collaborative working environment.
• Commitment to diversity, equity, and inclusion with active employee resource groups.
• A workplace culture with a lighthearted touch including food-themed humor and creatively named meeting rooms.

Work Model

HelloFresh embraces a flexible hybrid approach combining remote work flexibility with opportunities for in-office collaboration, requiring a minimum of two days per week onsite. This model prioritizes trust, personalized work arrangements, and team choice.

Additional Information

HelloFresh Canada integrates AI-enhanced recruitment technologies to streamline application processing, although final hiring decisions are human-made.
This is an active vacancy being recruited for.

Location: Toronto, ON
Salary Range: CAD 200000 to 300000 annually