Yobi is a rapidly growing Behavioral AI company on a mission to ethically democratize the benefits of data and AI. Since 2019, we have built one of the largest consented behavioral datasets in the United States, extending far beyond the walled gardens of Big Tech. Unlike traditional LLM companies, Yobi builds foundation models of human behavior grounded in real-world actions such as purchases and store visits. Our private-by-design modeling enables state-of-the-art personalization and decisioning for leading brands and agencies while protecting privacy, safety, and ethics.
🏢 About Yobi
Today, we are focused on bringing the performance of closed-web user acquisition to the open web and connected TV, giving brands walled-garden results without the walls. At our core, Yobi is building the behavioral intelligence layer for any system that makes a personalization decision.
🎯 The Role
As a Machine Learning Engineer focused on Inference and Serving at Yobi, you’ll design, optimize, and operate the systems that bring our Behavioral AI models to life in real time. You’ll work at the core of our production environment, turning trained models into performant, reliable, and continuously improving services that power our open-web and CTV products.
✅ Key Responsibilities
Design, optimize, and operate systems that bring Behavioral AI models to life in real time
Shape how models are packaged, versioned, rolled out, and observed across environments
Ensure every prediction is fast, accurate, and accountable
Build or scale production ML serving systems—handling versioning, rollouts, rollback strategies, and live experimentation
Write robust, high-performance code in Go, Rust, C++, or Java, and bridge to Python for model integration and analysis
Treat inference as a living system—monitoring drift, tracking model lineage, and ensuring observability from input to outcome
Make serving systems reproducible and portable without over-engineering them
Reason about model performance, interpret trade-offs, and work with researchers to make models more deployable
📌 Required Qualifications
Deep expertise in model deployment
Low-latency mindset with understanding of model graph optimization, quantization, caching, batching, and efficient feature retrieval
Systems fluency with robust, high-performance code in Go, Rust, C++, or Java
Operational maturity with monitoring drift, tracking model lineage, and ensuring observability
Infrastructure intuition with custom runtime design, model registries, or lightweight orchestration
Applied ML understanding with reasoning about model performance and interpret trade-offs
🎁 Benefits
Competitive Base Salary
Meaningful equity & financial upside - a real % of the company
Annual bonus target based on personal and company performance
Health, Dental, Vision available
Unlimited PTO - we care about impact, not tracking days you’re out
