Senior Software Engineer, Core Ex AI Team

About This Role

This role involves building and integrating intelligent systems at the intersection of backend engineering and applied machine learning within the Search and Personalization team. The engineer will design, train, and deploy lightweight models, and partner with Machine Learning Engineers to operationalize complex models at scale.

Responsibilities

• Design and implement backend features that incorporate ML/AI, developing enhancements to Instacart's systems using lightweight ML techniques.
• Collaborate with Machine Learning Engineers to integrate advanced research models into production services, handling software architecture for model serving and optimizing inference performance.
• Develop data-driven algorithms and heuristics to power features like "trending items" or "popular searches" using robust data pipelines.
• Implement and monitor evaluation metrics, designing offline evaluation methods and developing dashboards to track performance metrics in production.
• Maintain high engineering standards, writing unit and integration tests, conducting code reviews, and ensuring systems are scalable and maintainable.

Requirements

• 5 years of experience with software development in one or more programming languages
• 2 years of experience with machine learning algorithms and tools, or artificial intelligence
• Hands-on experience with fundamental ML concepts and tools
• Demonstrated ability to work in cross-functional teams and partnering with ML engineers, product managers, and data scientists
• Willingness to learn new AI technologies and adapt to the iterative, experiment-driven workflow of ML projects
• Strong SQL skills to derive insights from data

Qualifications

• Bachelor's or Master's degree in Computer Science (or related field), or equivalent experience.
• 5 years of experience with software development and 2 years with machine learning algorithms or AI.

Nice to Have

• Experience deploying ML models into high-traffic production environments
• Experience building data pipelines (batch vs. real-time) for ML features
• Ability to design systems that integrate ML components, covering areas such as model deployment, feature engineering, and update strategies
• Ability to design offline experiments and analyze results, with comfort in metrics such as precision/recall, AUC, or other evaluation techniques

Skills

* Required skills