Job Description
Are you ready to define the next era of intelligent systems? Nexus Future Systems is pioneering the frontier of Artificial Intelligence and Robotics, and we are looking for a visionary AI & Robotics Engineer to join our elite R&D division in San Francisco. In this role, you won't just build software; you will architect the brain of the machines that will operate alongside humans in the 2026 timeline and beyond.
Our mission is to bridge the gap between deep learning theory and physical world interaction. You will work on cutting-edge projects involving autonomous agents, natural language processing, and advanced sensor fusion. If you are obsessed with the future of technology and thrive in a fast-paced, high-impact environment, this is your opportunity to shape history.
Responsibilities
- Design, develop, and deploy robust machine learning models for autonomous navigation and decision-making systems.
- Collaborate with cross-functional teams of mechanical engineers, data scientists, and product managers to integrate AI into physical hardware.
- Optimize neural network architectures for real-time performance on edge devices and cloud infrastructure.
- Conduct cutting-edge research to push the boundaries of generative AI and humanoid robotics.
- Mentor junior engineers and conduct code reviews to ensure high standards of technical excellence.
- Stay ahead of the curve by evaluating emerging technologies like Large Language Models (LLMs) and reinforcement learning.
Qualifications
- Master’s or PhD degree in Computer Science, Robotics, Electrical Engineering, or a related technical field.
- Minimum of 5 years of professional experience in AI/ML engineering, with a focus on robotics or embedded systems.
- Proficiency in programming languages such as Python, C++, and ROS (Robot Operating System).
- Strong understanding of deep learning frameworks (TensorFlow, PyTorch) and optimization techniques.
- Demonstrated experience with sensor fusion, SLAM, or computer vision algorithms.
- Exceptional problem-solving skills and the ability to work in ambiguous, high-stakes environments.