Research Intern — Neural Network Training and Hardware–Software Co-Design

Summary:

We're looking for an intern to design and train neural networks that run efficiently on custom hardware for wearable and robotics devices. You'll co-design models and systems that run them under tight accuracy, latency, power, and memory budgets, and own the work end to end, from training through validation on real hardware, including FPGA prototypes.

Required Skills:

Research Intern — Neural Network Training and Hardware–Software Co-Design Responsibilities:

1. Design, train, and evaluate neural networks for on-device workloads under compute, memory, and energy constraints

2. Develop hardware-aware training and model compression techniques and measure their impact on target hardware

3. Explore partitioning models across multiple accelerators or chips, including how inter-chip communication affects accuracy and performance

4. Profile models end to end and use the measurements to drive both model and hardware design decisions

5. Prototype and validate on FPGA platforms, modifying and debugging existing RTL as needed

6. Present results through a working demo and a technical write-up

Minimum Qualifications:

Minimum Qualifications:

1. Currently pursuing a PhD in Computer Science, Electrical/Computer Engineering, Machine Learning, or a related field

2. Hands-on experience training deep neural networks in PyTorch or TensorFlow, from data pipeline through debugging and evaluation

3. Working knowledge of computer architecture: how memory hierarchy, data movement, and numerical precision affect neural network performance

4. Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

5. Intent to return to full-time degree program after completion of the internship

Preferred Qualifications:

Preferred Qualifications:

1. RTL design in Verilog or SystemVerilog, including simulation and testbenches

2. FPGA experience: synthesis, timing closure, and on-board bring-up and debug

3. Quantization-aware training, mixed precision, pruning, or knowledge distillation

4. Experience with neural network accelerators, model parallelism, or distributed inference

5. C/C++ and model deployment on embedded or edge platforms

6. Publications or substantial projects in efficient ML, ML systems, or computer architecture (e.g., MLSys, NeurIPS, ICLR, ISCA, MICRO, DAC)

Public Compensation:

$7,313/month to $12,667/month + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].