Robotics Lead AI - ( Senior Staff)

Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience. We are seeking experts with a robust background in the field of deep learning (DL) to design state-of-the-art low-level perception (LLP), end-to-end models and Vision-Language models(VLM)/ Vision-Language-Action models(VLA) for Autonomous Driving and Robotics use cases, with a focus on achieving accuracy-latency Pareto optimality. The ideal candidate must be well-versed in recent advancements in Vision Transformers (Cross-attention, Self-attention), lifting 2D features to Bird's Eye View (BEV) space, their applications to multi-modal fusion and VLM/VLA Models. The team is responsible for enhancing the speed, accuracy, power consumption, and latency of deep networks running on Snapdragon Ride AI accelerators. A thorough understanding of machine learning algorithms, particularly those related to Automotive and Robotics use cases is essential. Research experience in the development of efficient networks, various Neural Architecture Search (NAS) techniques, network quantization, and pruning is highly desirable. Strong communication and interpersonal skills are required, and the candidate must be able to work effectively with various horizontal AI teams. Candidates with a broad spectrum of experience, 12+ years in the relevant domain. Good at software development with excellent analytical, development, and problem-solving skills. Strong understanding of Machine Learning fundamentals Hands-on experience with deep learning network design and implementation. Ability to define network from scratch in PyTorch, ability to add new loss function, modify network with torch.fx. Adept at version control system like GIT. Experience in neural network quantization, compression, pruning algorithms. Experience in deep learning kernel/compiler optimization Strong communication skills Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations. Models, architects, and develops machine learning hardware (co-designed with machine learning software) for inference or training solutions. Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development. Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same. Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance from more experienced engineers. Conducts complex experiments to train and evaluate machine learning models and/or software independently. Works independently with minimal supervision. Decision-making may affect work beyond immediate work group. Requires verbal and written communication skills to convey information. May require basic negotiation, influence, tact, etc. Has a moderate amount of influence over key organizational decisions (e.g., is consulted by senior leadership to make key decisions). Tasks require multiple steps which can be performed in various orders; some planning, problem-solving, and prioritization must occur to complete the tasks effectively.