1 day ago
Base Salary
$173k - $219k/yr
Responsibilities
- Design, implement, and deploy machine learning models and services for Enterprise AI products and business initiatives.
- Own the full machine learning lifecycle, including problem formulation, data preparation, feature development, model training, evaluation, experimentation, deployment, rollout, and monitoring.
- Build reliable and scalable production software and operate machine learning services on cloud infrastructure.
- 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 requirements, metrics, priorities, and measurable outcomes.
- Contribute to architecture discussions, technical direction, engineering practices, mentoring, and operational support for critical services.
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, testing, profiling, debugging, and code review.
- Experience across the complete machine learning lifecycle and with production monitoring.
- Experience building and operating machine learning services or data products in Google Cloud Platform or Amazon Web Services.
- Experience with containerized services and production practices including Docker, continuous integration, monitoring, alerting, and incident response.
- Ability to collaborate across product, engineering, data science, and business teams to deliver measurable outcomes.
- Preferred qualifications include a Master’s or PhD, large-scale or low-latency ML experience, distributed data processing, streaming, feature stores, real-time feature computation, model serving, orchestration, and ML platforms.
- Preferred qualifications include experience with Kubernetes, Airflow, Spark, C++, Java, or Go; simulation or counterfactual evaluation; mentoring; technical leadership; or e-commerce, logistics, retail, marketplace, or advertising domains.
Benefits
- Remote Flex First work arrangement with flexibility to work from home, an office, or another preferred location, plus regular in-person events.
- Competitive location-dependent base compensation and benefits.
- Eligible for a new hire equity grant and annual refresh grants.
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.