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Technical Lead
2 months ago
Job Description
We are seeking an experienced Architect specialising in Computer Vision software to lead and shape our various development initiatives. The ideal candidate will have a proven track record in marrying deep knowledge and expertise in Computer Vision algorithms with end product realisations of these algorithms.
This role involves designing robust software architectures, integrating advanced algorithms, and optimising solutions for real-world UAV applications such as Vision based UAV navigation, object detection/tracking, obstacle avoidance, etc. In some cases this would require processing of not just camera but also other kinds of sensors such as radar, inertial, GPS, etc. Prior experience in developing such multi-modal architectures for applications such as Advanced Driver Assistance Systems (ADAS), Robotics or UAVs would be highly preferred.
Key Requirement & Responsibilities:
Deep Learning and Computer Vision Expertise:
- Lead the incorporation of advanced DL/CV algorithms into system architecture.
- Stay abreast of the latest trends and innovations in computer vision technology.
Architectural Design:
- Develop and articulate a clear software architecture for computer vision systems.
- Design scalable and modular software systems that align with business objectives.
Hardware Utilisation Strategy:
- Develop strategies for leveraging hardware capabilities to optimise software performance.
- Collaborate with hardware teams to align software and hardware development efforts.
Edge Computing Design:
- Define strategies for optimising deep learning inference on edge devices.
- Architect solutions for edge computing deployment, ensuring optimal performance on resource-constrained devices.
- Address challenges related to latency and real-time processing.
Cross-functional Collaboration:
- Collaborate with cross-functional teams, including hardware engineers, software developers, and researchers.
- Facilitate effective communication and coordination among team members.
Skills & Qualifications:
- Expertise in deep learning frameworks such as TensorFlow or PyTorch.
- Experience in edge computing and deploying solutions on embedded devices.
- Knowledge of ROS/ROS2 and hardware acceleration using OpenCL/CUDA is a plus.
- Publications in top CV/ML conferences is a plus.
- Understanding of software architecture principles and best practices.
- Excellent leadership and communication skills.
- Bachelor''s or Master''s degree in Computer Science, Electrical Engineering, or a related field.