Job Description
Are you ready to shape the future of intelligent systems? Nexus 2026 Technologies is at the forefront of the 2026 revolution, developing autonomous neural interfaces and predictive AI models that redefine human-machine interaction. We are seeking a visionary Senior AI & Robotics Engineer to lead our advanced R&D division in San Francisco.
In this pivotal role, you will not just write code; you will architect the brain of our next-generation robotic systems. We value deep technical expertise, creative problem-solving, and a passion for pushing the boundaries of what is possible in 2026 and beyond.
Why Join Us?
- Work on cutting-edge projects that define the 2026 era of technology.
- Competitive salary and equity package in a high-growth tech hub.
- Flexible remote-first hybrid work environment.
Responsibilities
- Architect Development: Design and implement scalable, fault-tolerant neural network architectures for autonomous robotics and real-time data processing.
- Research & Innovation: Spearhead research initiatives in predictive algorithms, deep reinforcement learning, and edge computing optimization.
- System Integration: Collaborate with hardware engineers to seamlessly integrate AI models with physical robotic systems.
- Mentorship: Lead a team of junior engineers and data scientists, conducting code reviews, technical workshops, and career development sessions.
- Performance Tuning: Optimize existing models for latency, accuracy, and resource efficiency to meet 2026 industry standards.
- Prototyping: Build rapid prototypes of complex AI modules to validate concepts before full-scale production.
Qualifications
- Education: Master’s or PhD in Computer Science, Robotics, Electrical Engineering, or a related technical field.
- Experience: 7+ years of professional experience in AI, Machine Learning, or Robotics, with a proven track record of shipping production-grade software.
- Technical Skills: Proficiency in Python, C++, TensorFlow, PyTorch, and CUDA.
- Knowledge: Deep understanding of Reinforcement Learning, Computer Vision, and Natural Language Processing (NLP).
- Tools: Experience with containerization (Docker/Kubernetes) and cloud platforms (AWS/Azure/GCP).
- Soft Skills: Strong leadership abilities, excellent communication skills, and a passion for solving complex engineering challenges.