Description:

Yobi is a rapidly growing Behavioral AI company focused on ethically democratizing the benefits of data and AI.
The company has built one of the largest consented behavioral datasets in the United States since 2019, extending beyond traditional Big Tech.
Yobi constructs foundation models of human behavior based on real-world actions like purchases and store visits.
The company’s private-by-design modeling enables advanced personalization and decision-making for brands while ensuring privacy, safety, and ethics.
Yobi aims to bring the performance of closed-web user acquisition to the open web and connected TV.
The role involves designing, optimizing, and operating systems that implement Behavioral AI models in real time.
Engineers at Yobi own significant areas of the architecture and culture, building systems from the ground up and defining the ethical scaling of Behavioral AI.
The company is well-funded with over five years of runway and is rapidly scaling revenue, projecting to break even by 2026.
Yobi has partnerships with Microsoft and Databricks and offers fully remote or hybrid work options from several hubs including SF Bay Area, Seattle, and NYC.
The team consists of Machine Learning experts with experience at leading tech companies like Amazon, Uber, Twitter, and Meta.

Requirements:

Candidates must have deep expertise in model deployment, having built or scaled production ML serving systems that handle versioning, rollouts, rollback strategies, and live experimentation.
A low-latency mindset is essential, with an understanding of model graph optimization, quantization, caching, batching, and efficient feature retrieval.
Candidates should possess systems fluency, writing robust, high-performance code in Go, Rust, C++, or Java, and be comfortable integrating with Python for model analysis.
Operational maturity is required, treating inference as a living system by monitoring drift, tracking model lineage, and ensuring observability from input to outcome.
Infrastructure intuition is necessary to create reproducible and portable serving systems without over-engineering, utilizing custom runtime design, model registries, or lightweight orchestration.
An applied ML understanding is important, allowing candidates to reason about model performance, interpret trade-offs, and collaborate with researchers to enhance model deployability.

The position offers a competitive base salary.
Employees receive meaningful equity and financial upside, representing a real percentage of the company.
There is an annual bonus target based on personal and company performance.
Health, dental, and vision insurance plans are provided, with most plans requiring little to no out-of-pocket expenses.
Employees enjoy unlimited PTO, emphasizing impact over tracking days off.
A 401k plan with company match is available to employees.

Skills

Benefits