Software Engineer, SystemsML, Training Frameworks & Inference Optimization
Seattle, WA | Burlingame, CA | New York City
The Core AI Model Optimization and Research (MORE) team is hiring SWEs to work on Model Optimization and Training Frameworks. The MORE team is a horizontal ML team under XRTech consisting of multiple pillars focusing on:
1. Training Frameworks and Training Efficiency
2. Model Optimization for On-Device Inference
3. Foundational On-Device Models.
Our team enables on-device models across Family of Apps, VR and AR, bringing the magic of AI to the edge. Along with our partners, we have shipped on-device SAM on IG and Full body Avatars on Quest-3. We also build and maintain the training framework (Vizard) used by multiple groups in XRTech for model development and optimization.Software Engineer, SystemsML, Training Frameworks & Inference Optimization Responsibilities
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.
1. Training Frameworks and Training Efficiency
2. Model Optimization for On-Device Inference
3. Foundational On-Device Models.
Our team enables on-device models across Family of Apps, VR and AR, bringing the magic of AI to the edge. Along with our partners, we have shipped on-device SAM on IG and Full body Avatars on Quest-3. We also build and maintain the training framework (Vizard) used by multiple groups in XRTech for model development and optimization.Software Engineer, SystemsML, Training Frameworks & Inference Optimization Responsibilities
- Optimize models for latency and power consumption for both on-device and GPU inference.
- Work closely with partner teams to help them meet quality, latency and complexity constraints on resource constrained devices.
- Build tools to automate model optimization and compression.
- Fine tune, quantize and deploy models on phones, AR and VR devices.
- Contribute to Vizard, a new framework built for training models targeted towards on-device use-cases.
- Ideate and implement new features in Vizard to improve developer experience and efficiency.
- Drive framework adoption by supporting migration of key training workloads into the framework.
- Support periodic oncall and help resolve user issues.
- Work with the Vizard team to improve reliability and efficiency of the framework.
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- Specialized experience in the following machine learning/deep learning domains: Model quantization, compression, on-device inference, GPU inference, PyTorch
- Masters/PhD degree in Computer Science, Computer Engineering or relevant technical field.
- Experience in building ML frameworks (Pytorch, Pytorch Lightning).
- Experience with distributed systems and optimizing resource utilization.
- Experience with accelerating deep learning models for on-device inference.
- Familiarity with on-device inference platforms (ARM, Qualcomm DSP).
- Optimizing machine learning model inference and training on NVIDIA GPUs.
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.
Tags: Computer Science Deep Learning Distributed Systems Engineering GPU Machine Learning ML models Model inference PhD Physics PyTorch Research VR
Perks/benefits: Career development Equity Health care Salary bonus
Region:
North America
Country:
United States
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Deep Learning Jobs
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