Description
At Instacart, we're transforming the grocery industry by delivering an essential service that customers rely on to get their groceries and household goods. We're seeking a Senior Machine Learning Engineer to design, build, and deploy production machine learning systems that create measurable business impact.
Overview
Our Enterprise AI organization builds intelligent products and platforms that help transform the grocery industry. You'll work across the full lifecycle of machine learning products, from problem formulation and data development through experimentation, deployment, monitoring, and continuous improvement.
Responsibilities
- Design, implement, and deploy machine learning models and services that support high-impact Enterprise AI products and business initiatives.
- Own the full machine learning lifecycle, including problem formulation, data preparation, feature development, model training, offline evaluation, experimentation, production rollout, and ongoing performance monitoring.
- Build reliable, scalable, and maintainable software in Python and related technologies, applying strong practices for testing, profiling, code review, documentation, and operational readiness.
- Partner with product, engineering, data science, and business stakeholders to define success metrics, prioritize work, and deliver solutions that improve customer and business outcomes.
- Develop and operate machine learning services on cloud infrastructure, with appropriate monitoring, alerting, observability, and safeguards for production performance and reliability.
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 experience writing production-quality code with automated testing, profiling, debugging, and code review practices.
- Experience with the complete machine learning lifecycle, including data preparation, feature engineering, model evaluation, experimentation, deployment, and production monitoring.
- Experience building and operating machine learning services or data products in a cloud environment such as Google Cloud Platform or Amazon Web Services.
Benefits
- Highly market-competitive compensation
- New hire equity grant and annual refresh grants
- Flexible remote work policy