Job Description
Are you ready to define the technological landscape of 2026 and beyond? Nexus Future Systems is seeking a visionary Senior AI/ML Architect to lead our next-generation research initiatives. We are building the foundation for the AI-driven reality of the future, and we need a technical mastermind to translate complex algorithms into scalable, transformative products.
As a Senior AI/ML Architect at Nexus, you won't just be maintaining legacy systems; you will be architecting the neural networks that will power the next decade of human-computer interaction. If you thrive on solving unsolved problems and pushing the boundaries of what is possible in Generative AI, Deep Learning, and Quantum Computing integration, we want to hear from you.
Why Join Us?
- Work at the forefront of Artificial General Intelligence (AGI) development.
- Competitive equity package and a culture that prioritizes innovation over bureaucracy.
- Top-tier hardware and compute resources for rapid prototyping.
- Collaborate with a world-class team of PhDs and industry veterans.
We are looking for someone who is not just an engineer, but a pioneer.
Responsibilities
- Architectural Leadership: Design and implement scalable, high-performance machine learning infrastructure capable of handling petabyte-scale data.
- Research & Development: Spearhead research into cutting-edge areas including Large Language Models (LLMs), Computer Vision, and Reinforcement Learning to prepare for the 2026 tech landscape.
- Model Optimization: Deploy and optimize AI models for production environments, ensuring low latency and high accuracy.
- Code Review & Mentorship: Establish coding standards and mentor junior engineers and data scientists to foster a culture of technical excellence.
- Cross-Functional Collaboration: Work closely with product managers and software engineers to translate business requirements into technical AI solutions.
- Ethical AI Compliance: Ensure all AI systems adhere to strict ethical guidelines and safety protocols.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related field (PhD preferred for research roles).
- Experience: 5+ years of professional experience in AI/ML engineering, with a proven track record of shipping production-ready models.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and modern MLOps tools (Docker, Kubernetes, MLflow).
- Domain Knowledge: Strong understanding of Neural Networks, Transformers, or Generative Adversarial Networks (GANs).
- Problem Solving: Demonstrated ability to tackle complex, ambiguous problems and derive innovative solutions.
- Communication: Excellent verbal and written communication skills, capable of presenting technical concepts to non-technical stakeholders.