Computer Vision Engineer

Principal Duties and Responsibilities

• Leverage advanced video and computer vision engineering expertise to research, design, and implement critical video processing and computer vision algorithms, including video encoder, decoder, processing, quality enhancement, and real‑time computer vision pipelines, from concept through production deployment.
• Lead system‑ and algorithm‑level architecture definition, standard studies, and feature decomposition to drive hardware and software requirements and specifications.
• Profile and optimize algorithm and model performance across memory, compute, power, and bandwidth constraints on mobile and embedded platforms.
• Collaborate closely with cross‑functional teams (hardware, software, systems, and product) and with customers to commercialize technologies and deliver best‑in‑class visual analytics experiences.
• Write clear and concise technical documentation, design specifications, and feature descriptions to guide internal teams and external partners.
• Contribute effectively in a fast‑paced, highly collaborative environment with globally distributed, cross‑functional teams.
• Provide technical mentorship and guidance to engineers across experience levels and influence technical decisions beyond the immediate team.

• Bachelor’s degree in Computer or Electrical Engineering, Computer Science, or a related field and 4+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
• Master’s degree in Computer or Electrical Engineering, Computer Science, or a related field and 3+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
• PhD in Computer or Electrical Engineering, Computer Science, or a related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

• Strong background in computer vision and video processing algorithms.
• Solid understanding of SoC architecture, including compute accelerators, memory hierarchies, and hardware/software interfaces.
• Hands‑on experience with modern deep learning architectures.
• Strong coding skills in Python and C/C++ for production-quality development, optimization, and on‑device deployment, with experience using ML/CV frameworks such as PyTorch, Tensor Flow, ONNX, and OpenCV.
• Familiarity with hardware modeling, FPGA prototyping, or RTL design is a plus.
• Strong ability to work across algorithm, software, and hardware boundaries.
• Experience with real‑time computer vision systems or embedded AI deployment.
• Experience using performance profiling tools and hardware simulators.

• Works independently with minimal supervision.
• Provides technical leadership, supervision, and guidance to other team members.
• Decision‑making impacts work beyond the immediate work group.
• Requires strong verbal and written communication skills; may require negotiation, influence, and tact.
• Has significant technical influence over key product, architecture, and organizational decisions.
• Tasks require multi‑step planning, prioritization, and problem‑solving, with flexibility in execution order to achieve objectives efficiently.

• Master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
• 4+ years of experience developing and implementing computer vision and video algorithms within system‑level products.
• 4+ years of experience with system design, system integration, and hardware/software optimization.
• 4+ years of experience with programming (C, C++, Python), computer architecture, or embedded systems.
• 3+ years of experience working in a large, matrixed organization.
• 1+ year of experience interacting with senior leadership (Director level and above).
• 1+ year of experience in a technical leadership role, with or without direct reports.
• Publication, patent, or external technical contribution experience is a plus.

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