Job Description
The Future is Here. Nexus Future Systems is pioneering the next era of cognitive computing. We are seeking a visionary Senior AI Architect to lead the development of our 2026-ready neural infrastructure. If you are passionate about building systems that think, learn, and evolve, we want to meet you.
About the Role:
As a Senior AI Architect, you will be at the helm of designing scalable, robust, and ethically sound AI models. You will bridge the gap between theoretical research and production-grade deployment, ensuring our platforms remain ahead of the curve in the rapidly evolving landscape of artificial intelligence.
Why Join Us?
- Work on cutting-edge technology that defines the future.
- Competitive compensation package including equity.
- Flexible remote-first culture with a hub in the heart of San Francisco.
Responsibilities
- Architectural Design: Design and implement next-generation neural network architectures capable of handling petabyte-scale data streams.
- Model Optimization: Enhance model inference speed and accuracy using advanced quantization and pruning techniques.
- Research Integration: Translate the latest academic research from top-tier conferences (NeurIPS, ICML) into practical, production-ready code.
- Ethical AI Governance: Establish frameworks to ensure AI transparency, fairness, and safety in all deployed models.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- System Scalability: Collaborate with DevOps teams to build resilient cloud-native AI pipelines on AWS and Azure.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a senior or architect-level role.
- Core Skills: Deep expertise in Python, PyTorch, TensorFlow, and CUDA.
- Specialization: Proven track record in Large Language Models (LLMs), Computer Vision, or Reinforcement Learning.
- Problem Solving: Exceptional ability to solve complex, ambiguous problems with innovative technical solutions.
- Communication: Excellent written and verbal communication skills for technical and non-technical stakeholders.