Machine Learning Engineer - Inference / Serving

Yobi; New York (NY); Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive Base Salary

Meaningful equity

Annual performance bonus

Comprehensive health benefits

Unlimited PTO

401k with company match

Job summary

A Behavioral AI company is seeking a Machine Learning Engineer to design and optimize systems for bringing their models to life. The role involves ensuring ML models are efficient and reliable, requiring experience in model deployment and robust coding skills. Candidates should be familiar with low-latency techniques and operational maturity in ML systems. This position can be remote or hybrid from several hubs.

Qualifications

• Deep expertise in model deployment and scaling production ML serving systems.
• Understand low-latency model inference techniques.
• Robust coding skills in Go, Rust, C++, or Java.
• Experience in monitoring and observing models.

Responsibilities

• Design, optimize, and operate systems for Behavioral AI models.
• Package, version, and roll out ML models in production environments.
• Ensure models are fast, accurate, and accountable.

Skills

Model deployment

Low-latency optimization

High-performance coding in Go, Rust, C++, Java

Monitoring model drift

Infrastructure design

Applied ML understanding

Job description

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.

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.

Working at Yobi

We’re at an inflection point—customer adoption is accelerating, but there’s still room to shape the architecture and culture from the ground up. Engineers here own major surface areas, build 0→1 systems in large-scale data and model infrastructure, and help define how Behavioral AI scales ethically and effectively.

Highlights:

• Well-funded with 5+ years of runway. At the same time, we are scaling revenue quickly and project to be breakeven in 2026.

• Partnerships with Microsoft and Databricks

• Fully remote or hybrid from several hubs (SF Bay Area, Seattle, NYC)

• World-class team of Machine Learning experts who worked on cutting edge infra and recommender systems @ Amazon, Uber, Twitter, Meta, etc.

• Product and Go-To-Market teams who have taken ideas from concept to 9 figure revenue streams

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 - most plans will pay little to 0 out of pocket

• Unlimited PTO - we care about impact, not tracking days you’re out

• 401k with company match %

About 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.

This is an applied ML systems role—equal parts engineering depth, deployment craft, and model intuition. You’ll shape how models are packaged, versioned, rolled out, and observed across environments, ensuring every prediction is fast, accurate, and accountable.

What it takes to succeed in this role:

• 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.

We prioritize attitude, culture, and general (technical) fit over matching perfectly into one of our job descriptions. If our mission and work resonates with you, we encourage you to apply. Tell us how you can help drive our products forward, even if you don’t feel like you are a perfect fit for some of the listings.