Job Description
Are you ready to define the technological landscape of 2026?
Nexus Future Systems is seeking a visionary Senior Artificial Intelligence Architect to lead our next-generation research division. In this pivotal role, you will be responsible for designing scalable, robust AI systems that will underpin our flagship products for the coming decade. You will work at the intersection of theoretical research and practical engineering, pushing the boundaries of what is possible with Large Language Models and predictive analytics.
Why Join Us?
We are not just building software; we are architecting the future. You will have the autonomy to experiment with cutting-edge technologies, mentor a team of elite engineers, and directly impact the strategic direction of our AI infrastructure. Our culture rewards innovation, critical thinking, and high-performance delivery.
Responsibilities
- Lead AI Strategy: Define and execute the architectural vision for our AI/ML platforms, ensuring scalability, security, and performance.
- Model Development: Design and train state-of-the-art deep learning models using Python, PyTorch, and TensorFlow to solve complex business problems.
- System Optimization: Oversee the deployment and MLOps lifecycle, implementing CI/CD pipelines to ensure high availability and real-time inference capabilities.
- Research & Innovation: Stay ahead of industry trends, evaluating new algorithms and hardware accelerators to maintain a competitive edge in the 2026 tech landscape.
- Team Mentorship: Mentor junior engineers and data scientists, conducting code reviews and technical architecture sessions.
- Cross-functional Collaboration: Partner with product managers and engineering teams to translate complex technical requirements into elegant solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field (or equivalent professional experience).
- Experience: 5+ years of experience in software engineering with a focus on machine learning and artificial intelligence.
- Technical Skills: Proficiency in Python, SQL, and experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
- Big Data: Strong understanding of distributed computing systems (Kubernetes, Spark) and cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Demonstrated ability to debug complex systems and optimize algorithmic efficiency.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex concepts to non-technical stakeholders.