Job Description
We are building the intelligent infrastructure for the year 2026 and beyond. Nexus Future Systems is seeking a visionary Senior AI/ML Engineer to lead the development of next-generation generative AI agents and multimodal systems.
In this pivotal role, you won't just be writing code; you will architect the future of human-machine interaction. We are looking for a technical leader who is passionate about pushing the boundaries of LLMs, vector databases, and autonomous agents. If you want to define the technological landscape of the coming decade, this is your opportunity.
Why Join Us?
- Future-Proof Tech Stack: Work with cutting-edge frameworks designed for the 2026 era, including advanced RAG (Retrieval-Augmented Generation) and Agentic AI workflows.
- Impact at Scale: Your models will power enterprise solutions used by millions, driving efficiency and innovation globally.
- Elite Team: Collaborate with Ph.D.-level researchers and industry veterans from top-tier tech giants.
Responsibilities
- Design, train, and deploy state-of-the-art Large Language Models (LLMs) and AI agents optimized for the 2026 tech landscape.
- Architect scalable machine learning pipelines using Python, PyTorch, and modern cloud infrastructure (AWS/GCP).
- Optimize model inference speeds and reduce latency for real-time applications.
- Implement rigorous testing and evaluation frameworks to ensure model accuracy, fairness, and safety.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Stay ahead of the curve on emerging AI trends and integrate them into our product roadmap.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related field, or equivalent practical experience.
- 5+ years of professional experience in Machine Learning, Deep Learning, or Artificial Intelligence.
- Proficiency in Python, PyTorch, TensorFlow, or JAX with a deep understanding of distributed computing.
- Extensive experience with NLP tasks, including fine-tuning, prompt engineering, and RAG architectures.
- Strong understanding of cloud-native development, containerization (Docker/Kubernetes), and MLOps practices.
- Proven track record of delivering production-ready AI models that significantly impact business metrics.