1 day ago
Remote, CanadaSenior
Responsibilities
- Design, implement, and deploy machine learning models and services for high-impact Enterprise AI products and business initiatives.
- Own the full machine learning lifecycle, including problem formulation, data preparation, feature development, training, evaluation, experimentation, deployment, monitoring, and continuous improvement.
- Build reliable, scalable, maintainable production software in Python and related technologies.
- Operate machine learning services on cloud infrastructure with monitoring, alerting, observability, and production safeguards.
- Use experimentation, statistical analysis, and causal or counterfactual evaluation to assess model quality and guide launches.
- Collaborate with product, engineering, data science, and business stakeholders to define metrics, prioritize work, and deliver measurable outcomes.
- Contribute to technical direction, design reviews, architecture discussions, mentoring, engineering practices, and operational support.
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 coding, automated testing, profiling, debugging, and code review.
- Experience with the complete machine learning lifecycle, including data preparation, feature engineering, evaluation, experimentation, deployment, and production monitoring.
- Experience building and operating machine learning services or data products in cloud environments such as Google Cloud Platform or Amazon Web Services.
- Experience with containerized services and production software practices, including Docker, continuous integration, monitoring, alerting, and incident response.
- Ability to work with product, engineering, data science, and business stakeholders to define requirements and deliver measurable outcomes.
- Preferred qualifications include a Master’s or PhD, large-scale or low-latency ML systems experience, distributed data processing, streaming, feature stores, real-time feature computation, model serving, orchestration, and ML platforms.
- Preferred qualifications include proficiency in C++, Java, or Go; experience with simulation, experimentation, or counterfactual evaluation; mentoring or technical leadership; and experience in e-commerce, marketplaces, logistics, retail, advertising, or similar domains.
Benefits
- Remote Flex First work arrangement, with hiring currently limited to Ontario, Alberta, British Columbia, and Nova Scotia.
- Market-competitive Canadian base pay and eligibility for a new hire equity grant and annual refresh grants.
- Benefits offerings are available according to Instacart’s location-based plans and policies.
Tech Stack
Categories
About Instacart
Instacart builds a grocery technology platform used by retailers and consumers for online shopping, delivery, and pickup. Its business spans a consumer marketplace, enterprise e-commerce and fulfillment software, and a retail media ads network, generating revenue from fees, subscriptions, software, and advertising. Founded in 2012 and headquartered in San Francisco, the company is publicly traded on Nasdaq and operates across the U.S. and Canada.