Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

Artificial Intelligence Hardware Engineer - Hybrid/Remote - NYC

No visa sponsorship available at this time.

Our client an up and coming innovative AI start-up is seeking a highly skilled and innovative Artificial Intelligence Hardware Engineer to join their dynamic team. In this role, you will be responsible for designing, developing, and optimizing hardware systems specifically tailored for artificial intelligence (AI) applications. The ideal candidate will have a strong background in computer engineering, deep learning, and hardware design, with a passion for pushing the boundaries of AI technology.

Responsibilities:

Collaborate with cross-functional teams to understand AI application requirements and hardware specifications.

Design and develop custom hardware architectures optimized for AI algorithms, including neural network accelerators, specialized processors, and system-on-chip (SoC) solutions.

Implement and optimize algorithms for hardware acceleration, utilizing techniques such as parallel processing, pipelining, and memory optimization.

Conduct performance analysis and benchmarking of AI hardware systems to ensure optimal efficiency and scalability.

Work closely with software engineers to integrate hardware solutions into AI frameworks and platforms.

Research and evaluate emerging technologies and industry trends in AI hardware design, staying abreast of advancements in deep learning algorithms, hardware accelerators, and system architectures.

Collaborate with external partners, vendors, and research institutions to drive innovation and develop cutting-edge AI hardware solutions.

Document design specifications, performance metrics, and implementation details for internal and external stakeholders.

Provide technical guidance and mentorship to junior engineers and contribute to the overall technical expertise of the team.

Requirements:

Bachelor's degree in Computer Engineering, Electrical Engineering, or related field. Master's or Ph.D. preferred.

Proven experience in hardware design, development, and optimization for AI applications, with a minimum of 3 years in a relevant role.

Proficiency in hardware description languages (e.g., Verilog, VHDL) and experience with hardware design tools and methodologies (e.g., FPGA, ASIC).

Strong understanding of deep learning algorithms and frameworks (e.g., TensorFlow, PyTorch) and their hardware implementation requirements.

Experience with hardware acceleration techniques and technologies (e.g., GPU, FPGA, ASIC) for AI inference and training.

Familiarity with system-level design considerations, including power management, thermal constraints, and performance optimization.

Excellent problem-solving skills and the ability to analyze complex technical challenges and propose innovative solutions.

Strong communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment.

Experience with project management and product development lifecycle is a plus.