We are a leading high-frequency trading firm that leverages cutting-edge technology and advanced quantitative strategies to achieve superior market performance. Our team of experts is dedicated to maintaining our competitive edge in the financial markets.

Job Description:

We are seeking a highly skilled Hardware Machine Learning Engineer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and optimizing hardware solutions to accelerate machine learning algorithms and models used in our trading strategies. This role requires a strong background in hardware engineering, machine learning, and a keen interest in financial markets.

Key Responsibilities:

• Design and implement hardware architectures to optimize machine learning model performance and efficiency.
• Develop and integrate FPGA, ASIC, or GPU-based solutions for accelerating machine learning workloads.
• Collaborate with software engineers and data scientists to deploy machine learning models on custom hardware platforms.
• Conduct performance analysis and optimization of hardware components to ensure low latency and high throughput.
• Stay updated with the latest advancements in hardware and machine learning technologies to drive innovation within the team.
• Troubleshoot and resolve hardware-related issues to maintain system stability and reliability.

Qualifications:

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related field.
• Proven experience in hardware design and development, particularly with FPGA, ASIC, or GPU technologies.
• Strong understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch).
• Proficiency in hardware description languages (e.g., VHDL, Verilog) and programming languages (e.g., C , Python).
• Experience with high-frequency trading systems or financial markets is a plus.
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.