We are seeking a Reinforcement Learning Engineer with experience manipulating virtual environments to train autonomous agents. This role focuses on the design of robust simulation environments, reward structures, and policy architectures that can navigate complex, multi-sensor landscapes. Key Responsibilities Cross-Functional Coordination: Work with partner ML and Annotation engineers and TPMs to spec out data, simulation, and training requirements.

We are seeking an experienced Tech Lead to grow out and lead a team of MLOps engineers, data scientists and annotation tooling developers who will be building the backbone of all Machine Learning applied research at the organization. On the one hand, data annotation, validation, split management, curation, and database management for a web-hosted game development platform. On the other, training orchestration, queue management, load balancing, failure recovery, observability.

We are seeking an experienced Tech Lead Manager/Engineering Manager to grow out and lead a forward-deployed team of Machine learning engineers who will be building applications for a graphically intensive simulation platform. This role will serve as the central facilitator for platform director requests for engineers with technical expertise. Key Responsibilities Stakeholder Management: Steward the end-to-end planning, execution, and delivery of the platform-deployed machine learning applications.

In this role, you’ll use C++ to build important software that powers machine learning, computer vision, and 3D modeling applications. This software will rely on mathematical concepts to analyze images and create realistic 3D models based on real-world data. You’ll get to work with the latest research in fields like artificial intelligence, computer vision, and computer graphics. To keep track of your code and changes, you’ll use Git.

NBCU’s Distribution engineering is responsible for the automation and reliability of NBCU’s Live sources. Reasonable for the delivery of 200+ NBC and Telemundo stations and Cable networks, and live events like sports, news and entertainment content to third party providers and Peacock. NBCU’s Distribution Engineering is looking to add a talented Site Reliability Engineer to be part of our Video Streaming team to build automation solutions to deploy and maintain applications, focusing on scalability, reliability and resiliency.

In this role, you’ll use C++ to build important software that powers machine learning, computer vision, and 3D modeling applications. This software will rely on mathematical concepts to analyze images and create realistic 3D models based on real-world data. You’ll get to work with the latest research in fields like artificial intelligence, computer vision, and computer graphics. To keep track of your code and changes, you’ll use Git.

We are seeking a Senior Data Scientist with experience manipulating large 2D and 3D media datasets. This role is centered on bridging the gap between raw data and high-quality machine learning inputs, requiring a blend of technical expertise and cross-functional leadership. Key Responsibilities Cross-Functional Coordination: Work with partner ML and Annotation engineers and TPMs to spec out data and training requirements.

We are seeking a Deep Learning Engineer with experience manipulating large 2D and 3D media datasets. In this role, you will implement core algorithms that sit at the intersection of computer vision and computer graphics, helping us turn high dimensional data into high-fidelity content. Key Responsibilities Algorithm Implementation: Implement core deep-learning, computer vision, and (inverse-)procedural modeling algorithms in Python. You will rely on mathematical techniques from linear algebra, probability, and geometry to build these systems.

We are seeking a Deep Learning Engineer with experience manipulating large 2D and 3D media datasets. In this role, you will implement core algorithms that sit at the intersection of computer vision and computer graphics, helping us turn high dimensional data into high-fidelity content. Key Responsibilities Algorithm Implementation: Implement core deep-learning, computer vision, and (inverse-)procedural modeling algorithms in Python. You will rely on mathematical techniques from linear algebra, probability, and geometry to build these systems.

We are seeking a Staff MLOps Engineer with experience building and scaling infrastructure for large 2D and 3D media datasets. You will be responsible for the "backbone" of our machine learning lifecycle, ensuring that our data pipelines are automated, reproducible, and performant at scale. Key Responsibilities Cross-Functional Coordination: Work with partner ML and Annotation engineers and TPMs to spec out infrastructure and training requirements. Pipeline Automation: Design and maintain robust CI/CD and CT (Continuous Training) pipelines for complex multimodal models.