FPGA Machine Learning Engineering - Graduate Intern
About The Position
We are seeking a talented and motivated FPGA Machine Learning Engineering Graduate Intern to join our dynamic team. Our mission is to develop innovative IP blocks and hardware solutions that enable customers to accelerate machine learning workloads on Altera FPGAs. As an intern, you will contribute to the development and evaluation of quantization schemes optimized for our hardware, empowering customers to achieve optimal performance and efficiency when deploying ML models on FPGAs. You will gain hands-on experience with the FPGA AI Suite, including both hardware and software stacks, and work closely with senior engineers to analyze, design, and implement enhancements that improve the performance of ML workloads on Altera FPGAs. This is an exciting opportunity to innovate at the intersection of hardware and machine learning in a collaborative and creative environment.
Requirements
- Currently pursuing a Master’s or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
- Solid understanding of digital hardware concepts (e.g., dataflow, pipelining, memory hierarchies).
- Foundational knowledge of machine learning algorithms, especially quantization techniques and their hardware implications.
- Experience with at least one of the following: FPGA design (using Verilog, VHDL, or High-Level Synthesis tools)
- Proficiency in C/C++, Python, or similar programming languages.
- Strong analytical and problem-solving skills.
- Ability to work effectively in a collaborative team environment.
- Excellent verbal and written communication skills.
Nice To Haves
- Experience with ML model deployment or inference on FPGA platforms.
- Exposure to Altera FPGAs or similar architectures.
- Knowledge of popular ML frameworks (e.g., TensorFlow, PyTorch) and their quantization workflows.
Responsibilities
- Contribute to the development and evaluation of quantization schemes optimized for hardware.
- Gain hands-on experience with the FPGA AI Suite, including both hardware and software stacks.
- Work closely with senior engineers to analyze, design, and implement enhancements that improve the performance of ML workloads on Altera FPGAs.
Benefits
- Performance-based incentive opportunities
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What This Job Offers
Career Level
Intern
