24 hours ago
Base Salary
$154k - $217k/yr
Responsibilities
- Design and implement scalable systems software for large-scale machine learning training and inference across distributed infrastructure.
- Profile and optimize compute, memory, and I/O performance in ML pipelines.
- Develop and maintain reliable ML runtime systems for scheduling, resource management, and execution.
- Collaborate with AI researchers and hardware teams to map deep learning architectures onto accelerated hardware.
- Own technical designs and evaluate correctness, performance, reliability, and maintainability trade-offs.
- Define and monitor service-level objectives, performance metrics, dashboards, and alerting for ML infrastructure.
- Implement automated testing, staged rollouts, feature flagging, A/B testing, and comprehensive documentation.
- Mentor engineers and contribute to code and design reviews.
- Partner with product, data science, and operations stakeholders to productionize ML research requirements.
- Improve developer tooling, automation, and engineering efficiency across the ML systems organization.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- At least 6 years of software engineering experience focused on systems software, ML infrastructure, or distributed computing.
- Experience designing and optimizing systems for large-scale machine learning training or inference.
- Experience with profiling, bottleneck identification, performance analysis, and low-level systems tuning.
- Experience building production-grade distributed systems with observability, monitoring, and incident response practices.
- Experience communicating technical decisions through design documents, architectural proposals, or stakeholder alignment.
- Preferred experience with PyTorch, TensorFlow, or JAX, including framework internals, operator development, or runtime optimization.
- Preferred experience with AI skill development, prompt/context engineering, agent orchestration, and AI-enabled workflow optimization.
- Preferred experience with compiler technologies or graph-level deep learning optimizations such as MLIR, LLVM, TVM, or XLA.
- Preferred experience with GPU or AI accelerator programming models such as CUDA, ROCm, or vendor-specific kernel libraries.
- Preferred experience implementing responsible AI practices, including bias mitigation, model quality evaluation, and AI risk assessment.
Benefits
- Annual base salary of $154,003 to $217,000, plus bonus, equity, and benefits.
- The posting does not specify a work arrangement or other practical logistics.
Tech Stack
PyTorchTensorFlow
Categories
About Meta
Meta builds social platforms and communication apps—including Facebook, Instagram, WhatsApp, and Messenger—and develops AR/VR hardware and software such as Quest to power immersive computing. It monetizes primarily through advertising tools for businesses, with additional revenue from devices and services, and operates a massive global infrastructure. Founded in 2004 and headquartered in Menlo Park, California, Meta Platforms, Inc. is a public company traded on Nasdaq under the ticker META.