Senior Software Engineer (Ads Quality)

Join Instacart's Ads Quality team as a Senior Software Engineer II, specializing in ML infrastructure. You'll work with a team of software and machine learning engineers to build state-of-the-art systems that optimize Ads performance throughout the ads serving funnel. Your expertise will drive the development of scalable training and serving infrastructure, enhancing advertising effectiveness and operational stability.

• Design, develop, and deploy machine learning infrastructure to tackle practical challenges in our complex marketplace while advancing the training and serving platform.
• Optimize training and serving funnel bottlenecks—profiling real systems and driving meaningful wins in throughput, cost, and latency, from GPU/accelerator utilization to tail latency at serving time.
• Lead the infrastructure foundation for our real-time sequential foundation model, including online sequence feature stores, streaming update paths, efficient long-context serving, and training pipelines that keep pace with rapidly evolving data.

• Have 3+ years of industry experience building ML infrastructure or using machine learning to solve real-world problems with large datasets
• Strong analytical and problem-solving skills
• Have a graduate degree (masters or PhD) in computer science, artificial intelligence, machine learning, operations research or equivalent self study and experience
• Eager to jump into domains, languages, and problem areas that might be new and unfamiliar
• Excellent communication skills (both verbal and written) and can collaborate with a diverse group of stakeholders across all levels
• 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)
• Deep expertise building, scaling and managing ML infrastructure for training and/or serving in production, with a strong understanding of modern machine learning systems and MLOps
• Have 5+ years of industry experience tech leading a team to build ML infrastructure or using machine learning to solve real-world problems with large datasets
• Demonstrated experience 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
• Hands-on experience with real-time / online feature processing and serving—streaming systems (e.g., Kafka, Flink), online feature stores, and low-latency retrieval on the request path
• Experience with sequential modeling, transformer architecture, and generative retrieval or building large scale online recommendation systems
• Experience serving large sequential or foundation models in low-latency, high-QPS production settings
• Experience in digital advertising platforms
• Familiarity with LLM integrations, prompt engineering, and productivity tooling