Job Description
Are you ready to define the technological landscape of 2026 and beyond? Nexus Future Systems is seeking a visionary Lead AI Architect to spearhead our next-generation neural infrastructure.
In this pivotal role, you will not simply maintain existing systems; you will architect the foundational technologies that will power the enterprise world for the next decade. You will work at the intersection of theoretical research and practical application, designing scalable AI ecosystems that solve complex, high-stakes problems with unprecedented efficiency.
We are looking for a self-starter who thrives in ambiguity and possesses a deep understanding of the trajectory of artificial intelligence. If you are passionate about building the future, we want to hear from you.
Responsibilities
- Architect Future-Proof Solutions: Design and implement scalable machine learning frameworks tailored for the 2026 enterprise landscape, focusing on agentic AI and autonomous systems.
- Lead R&D Initiatives: Spearhead research projects exploring the frontiers of Generative AI and Large Language Models to stay ahead of industry trends.
- Model Optimization: Engineer high-performance models that reduce latency and improve inference accuracy, ensuring real-time user experiences.
- Technical Mentorship: Mentor a team of junior data scientists and engineers, fostering a culture of continuous learning and innovation.
- Strategic Collaboration: Partner with product managers and engineering leads to translate business requirements into robust technical architectures.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of professional experience in software engineering and machine learning, with at least 3 years in a lead or architect role.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and modern MLOps pipelines (e.g., Kubeflow, MLflow).
- Domain Knowledge: Proven track record in NLP, Computer Vision, or Reinforcement Learning.
- Soft Skills: Exceptional communication skills with the ability to explain complex technical concepts to non-technical stakeholders.