Skip to content
NEXTMOVEFDE careers · United States

Staff Machine Learning Engineer, ML Infrastructure

Technologies

Pytorch · Ray Data · Ray Train · Ray · Spark · Flink · Flyte · Airflow · Python

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.

Read the job description
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 also supports large-scale model training, feature generation, and experimentation workflows that power production ML systems. To support this growth, we need strong technical ownership to ensure our ML pipelines remain reliable, scalable, and architecturally sound. We are seeking a staff ML engineer to design and evolve the large-scale offline platform. This role focuses on building reliable infrastructure for generating training datasets, orchestrating ML workflows, and enabling efficient, distributed model training at
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 also supports large-scale model training, feature generation, and experimentation workflows that power production ML systems. To support this growth, we need strong technical ownership to ensure our ML pipelines remain reliable, scalable, and architecturally sound. We are seeking a staff ML engineer to design and evolve the large-scale offline platform. This role focuses on building reliable infrastructure for generating training datasets, orchestrating ML workflows, and enabling efficient, distributed model training at scale. You will work closely with ML engineers and platform teams to ensure our pipelines can efficiently handle growing data volumes and increasingly complex training workloads. You will play a key role in shaping how model datasets are prepared as well as model training, validated, and delivered to distributed training systems, while ensuring the reliability, scalability, and performance of our offline ML platform. What you'll be doing Design and operate large-scale data pipelines that generat [... source excerpt omitted ...] ocessing and model training Experience building infrastructure for training data generation, dataset preparation, or ML feature pipelines Deep experience designing and operating production-grade data pipelines Strong programming skills in Python and experience working with large-scale distributed workloads Experience with modern data infrastructure (data lakes, warehouses, orchestration systems, streaming platforms) Strong systems thinking, with the ability to reason about performance, scalability, reliability, and cost tradeoffs in distributed systems Proven ability to lead technical direction and influence architectural decisions across teams without formal authority Addit [... 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. This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleag

How jobs are selected

Employer postings · Data from · Sources