Senior Machine Learning Engineer

Overview

About the Role:

As a senior machine learning engineer in the Ads Quality team, you'll work with a team of software and machine learning engineers to build state-of-the-art systems that optimize ad performance throughout the ads serving funnel, from retrieval to pricing. Building on Instacart’s unique data and market position, these systems create value for advertising partners, improve consumer experience, and directly contribute to Instacart's overall revenue / business success.

You'll have the unique opportunity to collaborate with a cross-functional team, turning diverse insights into powerful solutions that elevate advertising effectiveness. Your expertise will steer the development of sophisticated algorithms and machine learning models, driving performance gains across our advertising platform. Together, we'll build an ads ecosystem that not only serves millions but also excels in delivering value to users and advertisers alike.

About the Team:

Instacart Ads is transforming the online grocery shopping experience by seamlessly integrating advanced advertising solutions into our platform. The Ads Quality team is dedicated to delivering outstanding advertising outcomes by driving innovation and precision in response prediction, advertiser optimization, and ads auction processes. Our mission is to ensure relevance, fairness, and performance for all participants in the ad ecosystem. By leveraging terabytes of data and sophisticated machine learning algorithms, we build advanced predictive models that enhance user experience, drive advertiser success, and sustain a thriving ad ecosystem.  We're also at the forefront of integrating Large Language Models (LLMs), unlocking powerful new capabilities that are redefining how brands connect with consumers in the digital grocery space.

About the Job:

• Design, develop, and deploy machine learning solutions to tackle practical challenges in our complex marketplace while advancing the training and serving infrastructure. 
• Collaborate closely with product managers, data scientists, and other engineers to deeply understand business needs and create impactful ML applications.
• Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals.
• Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.
• Mentor junior engineers, set technical direction, and conduct thorough code reviews to ensure high code quality and maintainability. Lead by example in fostering a culture of continuous improvement and technical excellence.

About You:

Minimum Qualifications:

• Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience
• A deep understanding of machine learning algorithms and techniques, with fluency in modern research and literature
• Strong programming skills in software engineering (e.g., Python, Go), along with expertise in data manipulation using tools (SQL, Spark, and Pandas), and ML frameworks (Torch, Tensorflow, XGBoost)
• Strong analytical and problem-solving skills.
• Excellent communication skills (both verbal and written) and can collaborate with a diverse group of stakeholders across all levels 
• Demonstrated experience in using advanced algorithms or machine learning to deliver material business results

Preferred Qualifications:

• Have 5+ years of industry experience using machine learning to solve real-world problems with large datasets
• Experience in digital advertising platforms
• Experience with sequential modeling, transformer architecture, and generative retrieval or building large scale online recommendation systems
• Familiarity with LLM integrations, prompt engineering, and productivity tooling
• Demonstrated experience in solving complex model training and serving efficiency challenges, including optimizing training pipelines, reducing model training times, and improving serving architectures to enhance operational efficiency and scalability