We are currently seeking a machine learning performance modeling engineer to support the development of a custom machine learning software/hardware verticals and use cases optimized for AR/VR systems. As part of the machine learning performance modeling team, you will help build performance modeling and analysis toolchains for machine learning workloads. You will work in close collaboration with the groups developing the hardware, system software and SoCs for AR/VR devices.
Performance Modeling Engineer Responsibilities
- Lead power and performance modeling of IP components and use cases for SoC chips.
- Extract system-usage behavior of workloads and design micro-benchmarks.
- Lead thermal measurement, performance bottleneck analysis and power characterization.
- Perform modeling at the right level of abstraction given model purpose.
- Partner across disciplines to problem solve, build new methodologies and coordinate multiple initiatives.
- Ability to operate in a cross-functional environment.
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- Experience with programming (C++, SystemC-TLM), scripting (Python).
- Experience with power concepts, trade-offs and low power design principles.
- Experience with performance profilers and power measurement tools.
- Familiarity with Instruction Set Simulators (ISS), optimized assembly-level kernels (e.g., ARM, Tensilica).
- Experience with SoC Architecture, NoCs, memory subsystems, and heterogeneous compute principles.
- Experience creating and optimizing machine learning workloads.
Preferred Qualifications
- Bachelors degree in EE, CS or equivalent experience.
- 3+ years of experience with C++ programming.
- 2+ years of experience with SystemC/TLM2 programming.
- Experience with CV/ML algorithms.
- Computer architecture experience, including CPU and domain-specific/ML accelerators.
- Familiarity with power management principles, thermal and di/dt analysis, multi-voltage designs, DVFS and UPF concepts.
- Experience with thermally constrained power/performance optimization on embedded devices.
- Experience with bare-metal programming, micro-benchmarking, etc.
- Experience with gathering and interpreting performance counters using tools like perf, VTune, etc.
- Experience in building performance models for custom accelerator and SOC pipelines.
For those who live in or expect to work from California if hired for this position, please click here for additional information.
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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.
$142,000/year to $203,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
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