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# Software Engineer, SystemML - AI Networking

- **Company:** The Meta Game, Inc.
- **Location:** Menlo Park, CA, United States
- **Salary:** $154,003.0 - $217,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Nvidia CUDA, Computer Programming, Computer Engineering, Distributed Data Store, InfiniBand, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, AI Infrastructure, Graphics Processing Unit (GPU), High Performance Computing, Pytorch, Large Language Models, Prompt Engineering, Deep Learning, Information Technology, Machine Learning Operations
- **Published:** October 31, 2026
- **Apply:** https://www.juju.com/job/1_facebook2-1823307875501968

## About the Role

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 3.
Proven C/C++ and Python programming skills 4.
Proven track record of leading successful projects 5.
Experience leading cross-functional technical projects and communicating technical decisions to both technical and non-technical stakeholders 6.
Specialized experience in one or more of the following machine learning/deep learning domains: Distributed ML Training, GPU architecture, ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine Learning frameworks (e.g.
PyTorch) **Preferred Qualifications:** Preferred Qualifications: 7.
Experience with NCCL and distributed GPU performance analysis on RoCE/Infiniband 8.
Knowledge of GPU architectures and CUDA programming 9.
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 10.
Experience working with DL frameworks like PyTorch, Caffe2 or TensorFlow 11.
Experience in AI framework and trainer development on accelerating large-scale distributed deep learning models 12.
Experience with both data parallel and model parallel training, such as Distributed Data Parallel, Fully Sharded Data Parallel (FSDP), Tensor Parallel, and Pipeline Parallel 13.
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) 14.
PhD in Computer Science, Computer Engineering, or relevant technical field 15.
Knowledge of ML, deep learning and LLM 16.
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) 17.