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NEXTMOVEFDE careers · United States

Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad)

No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.

About Unity

Builds real-time 3D creation, deployment, ads, monetization, and commerce tools for developers making games and interactive experiences across platforms.

Public · 2000–5000 people

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Internal deployment & tooling · Evidence for this classification:

The opportunity Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company. Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform enables large-scale model training, feature generation, and experimentation workflows that power production ML systems. We’re looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems. You’ll help build and evolve the infrastructure that powers training data generation, ML workflows, and distributed model training. Working
More from the job description

The opportunity Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company. Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform enables large-scale model training, feature generation, and experimentation workflows that power production ML systems. We’re looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems. You’ll help build and evolve the infrastructure that powers training data generation, ML workflows, and distributed model training. Working closely with experienced engineers and researchers, you’ll contribute to systems that ensure our ML pipelines are reliable, scalable, and efficient. This role offers the opportunity to bridge research and production—translating advanced ideas into systems that operate at scale. What you'll be doing Build and maintain data pipelines that generate training datasets for machine learning models and experimentation Contribute to infrastructure that supports distributed training workflows (e.g., PyTorc [... source excerpt omitted ...] sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written e

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