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tools. Proven experience in digital hardware design using Verilog/SystemVerilog or equivalent HDLs. Sound knowledge of machine learning algorithms and their hardware implementation considerations
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programming languages, e.g. C/C++, Python. Experience with Machine learning technologies (e.g., LLM, and Machine Learning) is an advantage Experience with Hardware, e.g., FPGA acceleration, is an
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programming languages, e.g. C/C++, Python. Experience with Machine learning technologies (e.g., LLM, and Machine Learning) is an advantage Experience with Hardware, e.g., FPGA acceleration, is an
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harness the capabilities of AI accelerator for machine learning and deep learning tasks. • Publish research findings in high-impact journals and present at international conferences. • Mentor
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, to develop advanced computational solutions for medical imaging applications. Key Responsibilites Research & Method Development Develop novel artificial intelligence and machine learning approaches
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and perception o Machine learning or reinforcement learning o Sensor fusion and state estimation o Motion planning and control • Excellent programming
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, physics, or statistics. At Jane Street, we take a rigorous, quantitative approach to trading on global markets, combining techniques from machine learning, distributed systems, programmable hardware
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. Familiarity with robotic middleware (e.g., ROS, MoveIt) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience
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and unmanned aerial vehicle development, in particular electronic hardware design and embedded system development. - Comprehension of common machine learning algorithms and image analysis
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with a passion for solving complex problems at the intersection of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical