Job Description
Are you ready to architect the future of technology? NexusCore Systems is a leading innovator in predictive AI and spatial computing, and we are seeking a visionary Senior AI & Future Tech Engineer to join our elite team in San Francisco. We are currently building the roadmap and technical foundation for our major 2026 product launch.
In this role, you won't just be maintaining legacy systems; you will be designing the next generation of neural interfaces and autonomous algorithms. You will work closely with our product strategists to translate futuristic concepts into scalable, production-ready code. If you are passionate about the bleeding edge of AI and want to define the tech landscape of 2026, this is your opportunity to make an impact.
Why Join Us?
- Work on high-impact projects that define the next decade of tech.
- Competitive compensation and equity package for top-tier talent.
- Flexible remote-first culture with a hub in the heart of SF.
- Access to cutting-edge hardware and research resources.
Responsibilities
- Architect and deploy advanced machine learning models tailored for the 2026 Tech Stack requirements.
- Lead the optimization of neural networks to ensure sub-millisecond latency for real-time applications.
- Collaborate with cross-functional teams to integrate generative AI capabilities into consumer-facing products.
- Mentor junior engineers and establish best practices for scalable AI infrastructure.
- Research emerging technologies (e.g., neuromorphic computing) to stay ahead of the 2026 industry curve.
- Perform rigorous code reviews and ensure system reliability across distributed cloud environments.
Qualifications
- Master’s degree in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience).
- Minimum of 5+ years of professional experience in AI/ML development and software engineering.
- Deep proficiency in Python, PyTorch, and TensorFlow.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Proven track record of deploying large-scale models to production environments.
- Excellent problem-solving skills with a focus on performance optimization.
- Experience with Natural Language Processing (NLP) or Computer Vision is a plus.