Über
Responsibilities
Analyze and design effective compiler passes and optimizations. Implement and/or enhance code generation targeting machine learning accelerators
• Work with algorithm research teams to map ML graphs to hardware implementations, model data-flows, create cost-benefit analysis and estimate silicon power and performance
• Work with hardware architects to co-design hardware features that maximize performance, power efficiency and programmability
• Contribute to the development of machine-learning libraries, intermediate representations, export formats, and analysis tools
• Analyze and improve the efficiency, scalability, and stability of our toolchains. Optimize and tune kernels and compiled code to achieve latency targets for ML inference
• Conduct design and code reviews. Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues
• Interface with other compiler-focused teams to evaluate and incorporate their innovations and vice versa
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 2+ years experience developing compilers, toolchains, runtime, or similar code optimization software
• Experience in software design and programming experience in Python and/or C/C++ for development, debugging, testing and performance analysis
• Experience in AI framework development or accelerating models on hardware architectures (GPU, TPU, custom AI ASICs)
Preferred Qualifications
• Experience working and communicating cross functionally in a team environment
• Experience with machine-code generation or compiler back-ends for on-device inference workloads
• Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, GCC, MSVC, Glow
• Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, recurrent networks, etc
• Experience developing high-performance kernels or runtime components and tuning them for inference specific accelerator platforms
• Experience of developing in a mainstream machine-learning framework, e.g. PyTorch, MLIR, Tensorflow or Caffe
About Meta
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.
Equal Employment Opportunity
Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.
Sprachkenntnisse
- English
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