Remote Senior Systems Engineer — C++/Python for ML & 3D

IuVe; United States; Remote; USD 175,000 - 215,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) Plan

Paid leave

Job summary

NBCUniversal is seeking a Senior Systems Engineer (C++/Python) for a remote opportunity. You will build software powering ML, computer vision, and 3D modeling, using C++, Python, and modern tools on Linux/macOS with Git for version control. Collaboration with leadership to align with product vision is essential.

Salary range USD 175,000–215,000 and comprehensive benefits are offered. You’ll deploy and test on large-scale geospatial data, optimize for speed and scalability, and work in a

Qualifications

• Bachelor’s Degree in Computer Science, Engineering, Mathematics, or related field.
• 3+ years of experience in a fast-paced tech environment.
• Strong C++ performance, scalability, and resource management.
• Experience with Git and Unix shell.
• Experience in ML, computer vision, or graphics is a plus.

Responsibilities

• Implement core ML/vision and (inverse-) procedural modeling algorithms in C++.
• Apply cutting-edge research in ML, CV, and graphics.
• Work with leadership to understand product vision and customer requirements.
• Deploy and test code on large-scale geospatial datasets.
• Interact with remote machines via Unix shell and collaborate with cross-functional teams.

Skills

C++

Python

Machine Learning

Computer Vision

3D Modeling

Git

Unix Shell

Linux

macOS

CMake

Education

Bachelor’s Degree in CS/Engineering/Math

Tools

Git

Mercurial

CMake

Job description

NBCUniversal is seeking a Senior Systems Engineer (C++/Python) for a remote opportunity. You will build software powering ML, computer vision, and 3D modeling, using C++, Python, and modern tools on Linux/macOS with Git for version control. Collaboration with leadership to align with product vision is essential.

Salary range USD 175,000–215,000 and comprehensive benefits are offered. You’ll deploy and test on large-scale geospatial data, optimize for speed and scalability, and work in a