Job Description
Shape the Intelligence of the Future
Are you ready to architect the systems that will define the technological landscape of 2026? Nexus Horizon Systems is seeking a visionary Senior AI & Neural Architecture Engineer to join our elite team in San Francisco. We are not just building software; we are building the brain of the next generation of sentient machines.
In this high-impact role, you will spearhead the development of scalable, general-purpose AI models and advanced neural interfaces. You will work directly with top-tier researchers to push the boundaries of Deep Learning, LLMs, and Reinforcement Learning. If you are a builder who thrives on complexity and wants to leave a permanent mark on the future of technology, we want to hear from you.
Responsibilities
- Architect Next-Gen AI Models: Design and implement cutting-edge neural network architectures capable of handling complex, real-time data streams and autonomous decision-making processes.
- Optimize Inference Systems: Lead efforts to reduce latency and improve the efficiency of AI inference on both cloud and edge devices, ensuring our models are faster and more cost-effective.
- Lead Technical Strategy: Define the long-term roadmap for AI research and development, collaborating with cross-functional teams to integrate AI capabilities into core product offerings.
- Model Training & Fine-Tuning: Oversee the training pipelines for large language models, utilizing advanced techniques to enhance accuracy, reduce hallucinations, and improve context retention.
- Peer Mentorship: Guide junior engineers and data scientists, fostering a culture of innovation, code excellence, and continuous learning within the engineering department.
- Research & Development: Stay ahead of the curve by exploring emerging paradigms such as Neuromorphic Computing and Quantum Machine Learning.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, Physics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Technical Mastery: Deep expertise in Python, C++, and modern ML frameworks (PyTorch, TensorFlow, JAX).
- Experience: 7+ years of professional experience in AI/ML engineering, with a proven track record of deploying production-grade models.
- System Design: Strong understanding of distributed systems, high-availability architecture, and cloud infrastructure (AWS, GCP, or Azure).
- Language Proficiency: Fluency in English; proficiency in additional languages is a plus.
- Innovation Mindset: Demonstrated ability to think creatively about complex problems and implement novel solutions.