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Yobi AI · 1 month ago

Machine Learning Engineer - Inference / Serving

United States

Full-time

Remote

Mid, Senior Level

Yobi AI is a rapidly growing Behavioral AI company focused on ethically democratizing the benefits of data and AI. The Machine Learning Engineer will design, optimize, and operate systems that bring Behavioral AI models to life in real time, ensuring fast, accurate, and accountable predictions.

Artificial Intelligence (AI)Machine LearningSoftware

Responsibilities

Design, optimize, and operate the systems that bring our Behavioral AI models to life in real time

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

Shape how models are packaged, versioned, rolled out, and observed across environments, ensuring every prediction is fast, accurate, and accountable

Qualification

Model deploymentLow-latency inferenceHigh-performance codingOperational maturityInfrastructure designApplied ML understandingGoRustC++JavaPython

Required

Deep expertise in model deployment. You've built or scaled production ML serving systems—handling versioning, rollouts, rollback strategies, and live experimentation

Low-latency mindset. You understand what makes inference fast: model graph optimization, quantization, caching, batching, and efficient feature retrieval

Systems fluency. You write robust, high-performance code in Go, Rust, C++, or Java, and are comfortable bridging to Python for model integration and analysis

Operational maturity. You treat inference as a living system—monitoring drift, tracking model lineage, and ensuring observability from input to outcome

Infrastructure intuition. You know how to make serving systems reproducible and portable without over-engineering them, whether that's through custom runtime design, model registries, or lightweight orchestration

Applied ML understanding. You can reason about model performance, interpret trade-offs, and work with researchers to make models more deployable