Job Description
We are on the cusp of a revolution in artificial intelligence, and Nexus 2026 is leading the charge. We are seeking a visionary Senior AI Architect to design the neural frameworks that will define the next decade of human-machine interaction.
In this pivotal role, you will bridge the gap between theoretical research and production-grade systems. You won't just be writing code; you will be architecting the brain of our autonomous ecosystem, ensuring scalability, efficiency, and ethical alignment.
Why Join Nexus 2026?
- Work at the intersection of Generative AI and Edge Computing.
- Competitive equity package and top-tier healthcare benefits.
- Flexible remote-first culture with quarterly in-person innovation sprints.
If you are ready to shape the landscape of technology in 2026 and beyond, we want to hear from you.
Responsibilities
- Architect Advanced AI Models: Design and implement scalable deep learning architectures for NLP, Computer Vision, and Predictive Analytics.
- Optimization & Performance: Fine-tune models for low-latency inference on edge devices, ensuring real-time responsiveness.
- Research Integration: Translate cutting-edge academic research into robust, production-ready software solutions.
- Mentorship: Lead a team of junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Infrastructure Strategy: Collaborate with DevOps to build robust MLOps pipelines for model training and deployment.
- Roadmap Planning: Define the technical roadmap for AI initiatives aligned with our 2026 strategic vision.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years of professional experience in software development with a focus on AI/ML.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (Apache Spark, Ray).
- Domain Knowledge: Deep understanding of Transformer models, Large Language Models (LLMs), or Reinforcement Learning.
- Problem Solving: Proven track record of solving complex, ambiguous problems in high-scale environments.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.