Job Description
Are you ready to shape the future of autonomous systems? NexusMind Robotics is seeking a visionary Senior AI Engineer to join our core research and development team in the heart of San Francisco. In this role, you will architect cutting-edge neural networks and drive the implementation of scalable machine learning models that power the next generation of robotic intelligence.
You will work alongside industry-leading researchers to solve complex problems in computer vision, natural language processing, and reinforcement learning. We offer a culture of high-impact engineering, rapid iteration, and radical transparency.
Responsibilities
- Design, train, and deploy advanced deep learning architectures for real-time robotic perception.
- Lead the end-to-end development of AI pipelines from data collection and labeling to model deployment.
- Optimize neural network performance for edge computing environments with strict latency requirements.
- Collaborate with cross-functional software and hardware engineering teams to integrate AI models into robotics systems.
- Conduct code reviews and mentor junior engineers on best practices in ML engineering and system architecture.
- Analyze large datasets to uncover patterns, refine model accuracy, and improve system reliability.
- Present research findings and architectural decisions to stakeholders and technical leadership.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field.
- Minimum of 5+ years of professional experience in machine learning and software engineering.
- Expert-level proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Deep understanding of linear algebra, probability, and optimization algorithms.
- Proven track record of deploying machine learning models into high-scale production environments.
- Experience with GPU-accelerated computing (CUDA) and edge deployment technologies.
- Strong problem-solving skills and the ability to thrive in a fast-paced, research-driven environment.