(09/10/2025) AI/ML Developer

Job Description Company Overview We are a innovative technology company specializing in embedded AI solutions. Our team develops cutting-edge applications for resource-constrained environments, leveraging hardware like NVIDIA Jetson-compatible System on Modules (SOMs) to deliver real-time AI capabilities across various industries. Job Summary We are seeking a talented AI/ML Developer to join our embedded systems team. In this role, you will focus on developing and optimizing AI models for deployment on NVIDIA Jetson-compatible SOMs. Your work will involve training models using reinforcement learning techniques, creating custom models that integrate vision, network, and system data, and incorporating voice interactions for enhanced user experiences. This position requires a blend of machine learning expertise, embedded software development skills, and a passion for pushing the boundaries of AI in constrained environments. Key Responsibilities - Design, develop, and train custom AI/ML models using reinforcement learning frameworks to solve complex problems in embedded applications. - Integrate multimodal data sources, including computer vision (e.g., image/video processing), network telemetry, system logs, and voice interactions, into cohesive models. - Optimize models for performance on NVIDIA Jetson-compatible SOMs, ensuring low latency, power efficiency, and real-time inference capabilities. - Collaborate with cross-functional teams (e.g., hardware engineers, software developers) to deploy models in embedded environments, including testing and debugging on physical hardware. - Conduct experiments to evaluate model performance, iterate on architectures, and implement techniques like model compression, quantization, and edge-specific optimizations. - Stay updated on advancements in AI/ML, reinforcement learning, and embedded computing, applying them to improve our solutions. - Document code, models, and processes to ensure reproducibility and knowledge sharing within the team. Required Qualifications - Bachelor's or Master's degree in Computer Science, Electrical Engineering, AI/ML, or a related field (PhD preferred for senior roles). - 3+ years of experience in AI/ML development, with a focus on reinforcement learning (e.g., using libraries like Stable Baselines, RLlib, or custom implementations). - Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Keras. - Hands-on experience with embedded systems, particularly NVIDIA Jetson platforms (e.g., Jetson Nano, Xavier, Orin) and compatible SOMs. - Strong knowledge of computer vision (e.g., OpenCV, YOLO, CNNs) and processing multimodal data (vision, network/system metrics, audio/voice). - Familiarity with voice interaction technologies (e.g., speech-to-text, natural language processing using libraries like SpeechRecognition or Hugging Face Transformers). - Experience in model optimization for edge devices, including techniques like pruning, distillation, and TensorRT integration. - Solid understanding of software engineering principles, version control (e.g., Git), and agile development methodologies. Preferred Skills - Experience with real-time operating systems (RTOS) or Linux-based embedded development. - Knowledge of networking protocols and system-level data integration for AI applications. - Background in robotics, IoT, or autonomous systems where embedded AI is applied. - Publications or contributions to open-source projects in AI/ML or embedded computing. - Ability to work in a fast-paced, collaborative environment with strong problem-solving skills. What We Offer - Competitive salary. - Opportunities for professional growth and working on impactful projects. - Flexible work environment with access to state-of-the-art hardware and tools. - A collaborative team culture focused on innovation and work-life balance. If you are passionate about AI in embedded domains and ready to tackle challenging problems with reinforcement learning and multimodal models, apply now Please submit your resume and a cover letter highlighting relevant experience.