Job Description
The Future is Now. Are You Building It?
Nexus Future Labs is at the forefront of the 2026 AI revolution. We are seeking a visionary Generative AI Architect to lead the development of next-generation Large Language Models (LLMs) and autonomous agents. If you are passionate about pushing the boundaries of artificial intelligence and shaping the digital landscape of tomorrow, we want to hear from you.
In this role, you will design and deploy scalable AI systems that redefine human-computer interaction. You will work in a high-performance environment, collaborating with top-tier engineers and researchers to solve complex problems in natural language processing, computer vision, and multi-modal AI.
Why Join Us?
- Work on cutting-edge projects that define the industry standard for 2026.
- Competitive compensation package and equity options.
- Flexible remote-first culture with state-of-the-art equipment.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art Generative AI models using transformer architectures and deep learning frameworks.
- System Architecture: Lead the architectural design for scalable inference pipelines, ensuring high throughput and low latency for real-time applications.
- Optimization: Implement model quantization, pruning, and distillation techniques to optimize models for edge devices and cloud environments.
- Research Integration: Stay ahead of the curve by integrating the latest research findings from top-tier conferences (NeurIPS, ICML) into production systems.
- Ethical AI: Establish and enforce guidelines for responsible AI, ensuring fairness, transparency, and safety in all model outputs.
- Collaboration: Partner with product managers and data scientists to translate technical capabilities into user-centric features.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related technical field.
- Experience: 5+ years of professional experience in machine learning, with at least 3 years specifically in Generative AI or NLP.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and CUDA. Deep understanding of Transformer models (BERT, GPT, LLaMA).
- System Design: Strong experience with distributed systems, Kubernetes, and cloud infrastructure (AWS/GCP/Azure).
- Mathematical Foundation: Solid grasp of linear algebra, calculus, probability, and statistics.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.