Senior Engineering Manager, ML Platform

📋 Description

• • As a Senior Engineering Manager for the ML Platform at Whatnot, you will be at the forefront of shaping the future of artificial intelligence and machine learning within one of North America and Europe's fastest-growing e-commerce platforms. This is a hands-on leadership role for intellectually curious and deeply technical individuals who are passionate about building and scaling the core infrastructure that powers our AI and ML initiatives. You will work closely with machine learning scientists to bring cutting-edge models, including self-hosted large language models, into production, unlocking entirely new product experiences and enhancing existing ones.
• • Your primary responsibility will be to lead the development and scaling of robust, dependable, and fast ML infrastructure. This encompasses a wide range of critical systems, from low-latency deep learning model serving and real-time streaming feature ingestion to distributed training pipelines and high-throughput GPU inference. This management role demands significant technical depth; you should be comfortable diving into the technical details, providing constructive architectural feedback, and contributing to code development at least one day a week.
• • You will own the end-to-end infrastructure that supports AI and ML models across all critical business functions. This includes driving growth through personalized recommendations, ensuring trust and safety on the platform, mitigating fraud, and enhancing seller tooling. Your work will directly impact the user experience and the overall dynamics of our marketplace.
• • A key aspect of your role will be to guide the prototyping, deployment, and productionization of novel ML architectures. You will be instrumental in designing and scaling inference infrastructure that can efficiently serve large, complex models with low latency and high throughput, ensuring a seamless experience for our users.
• • You will oversee and continuously evolve our real-time feature pipelines. These pipelines are crucial for feeding both online and offline systems, providing single-second feedback from user behavior, ensuring high reliability, and maintaining model training fidelity. This involves optimizing data ingestion and processing to support near-realtime feature generation.
• • Furthermore, you will drive improvements to our feature platform, expanding its capabilities beyond ML use cases to include areas like fraud rule management, where point-in-time backtesting is essential for accuracy and effectiveness.
• • Leading the development of distributed training and inference pipelines is another core responsibility. You will leverage GPUs and implement both model and data parallelism techniques to accelerate the training and deployment of sophisticated ML models.
• • Performance optimization will be a continuous focus. You will manage resource utilization effectively and develop intelligent feature caching strategies to ensure our ML systems operate at peak efficiency.
• • To empower our machine learning scientists, you will build essential abstractions, APIs, and developer tools. These will simplify the process of developing near-realtime features and iterating on models, allowing scientists to move faster and focus on innovation.
• • You will be responsible for rolling out improved developer ergonomics for model training and deployment, making the ML lifecycle smoother and more efficient for the entire team.
• • This role encourages you to stretch beyond your comfort zone, embracing new technical challenges as we continue to scale AI capabilities across Whatnot's diverse ecosystem. Your ability to adapt and learn will be key to success.
• • We offer flexibility in how you work, with options for remote or co-located work in our global hubs. However, team members in this role must reside within commuting distance of our New York, Seattle, Los Angeles, or San Francisco hubs to facilitate in-person collaboration for planning, problem-solving, and team connection.
• • This is an opportunity to make a significant impact on a rapidly growing platform, working with a talented team dedicated to building the future of commerce.