Instacart is hiring a Senior ML Engineer Fulfillment in Toronto!
Instacart is hiring a Senior Machine Learning Engineer to join its Enterprise AI group, working on intelligent products and platforms that support grocery delivery for customers, shoppers, retailers, and brand partners. The position is based in Toronto but is remote-friendly under the company's Flex First policy, with hiring limited to candidates residing in Ontario, Alberta, British Columbia, and Nova Scotia. The engineer in this role owns machine learning systems end to end: framing the problem, preparing data and features, training and evaluating models, running experiments, shipping to production, and monitoring performance after launch. Because the team sits at the intersection of AI and business operations, the work requires close collaboration with product managers, data scientists, platform engineers, and business stakeholders, turning loosely defined opportunities into dependable, scalable services. Instacart emphasizes a fast-moving environment where priorities and data shift frequently, so the ideal candidate is comfortable with ambiguity, can balance strategic thinking with hands-on coding, and is motivated by measurable impact. The role also carries a mentorship and technical-leadership component, including design reviews, architecture discussions, and helping shape engineering practices across the team. Compensation is listed as $180,000 to $190,000 CAD base, with eligibility for new-hire equity and annual refresh grants.
Key responsibilities
- Design, build, and ship machine learning models and production services supporting Enterprise AI products and business initiatives
- Own the entire model lifecycle, from problem framing and data preparation through feature engineering, training, offline evaluation, experimentation, rollout, and post-launch monitoring
- Write reliable, maintainable Python code with strong testing, profiling, review, documentation, and operational-readiness practices
- Work with product, engineering, data science, and business partners to set success metrics, sequence work, and deliver measurable outcomes
- Run ML services on cloud infrastructure with monitoring, alerting, observability, and safeguards for reliability and performance
- Apply experimentation, statistical analysis, and causal or counterfactual evaluation to judge model quality and inform launch decisions
- Influence technical direction through design reviews, architecture discussions, and evaluation of modeling and infrastructure tradeoffs
- Strengthen the engineering culture by sharing knowledge, mentoring teammates, refining development practices, and supporting critical services operationally
Key requirements
- Bachelor's degree in computer science, engineering, mathematics, statistics, or a related technical field, or equivalent practical experience
- Five or more years of professional experience developing and deploying machine learning models or systems in production
- Proficiency in Python and SQL, including production-quality code with automated testing, profiling, debugging, and code review
- Hands-on experience across the full ML lifecycle: data preparation, feature engineering, model evaluation, experimentation, deployment, and production monitoring
- Experience building and operating ML services or data products on a cloud platform such as Google Cloud Platform or AWS
- Familiarity with containerized services and production practices including Docker, continuous integration, monitoring, alerting, and incident response
- Proven ability to collaborate with product, engineering, data science, and business stakeholders to define requirements and deliver results
- Preferred: master's or PhD in a quantitative field; large-scale, high-throughput, or low-latency ML systems; distributed processing, streaming, feature stores, or real-time features; Kubernetes, Airflow, Spark, or similar ML platform tooling; simulation or counterfactual evaluation frameworks; C++, Java, or Go; mentoring or technical leadership; e-commerce, marketplace, logistics, retail, or advertising domain experience
- Seniority: Senior
- Work mode: Remote (Flex First; hiring in Ontario, Alberta, British Columbia, and Nova Scotia)
- Salary: $180,000 - $190,000 CAD
- Key skills: Python, SQL, Machine Learning, Cloud (GCP/AWS), Docker, CI/CD, Monitoring and Alerting, Experimentation, Kubernetes, Airflow, Spark, Feature Engineering, Model Deployment, Distributed Data Processing, C++
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