Job Description
Are you ready to build the future? Nexus Future Labs is seeking a visionary Senior AI Architect to lead the development of next-generation artificial intelligence systems designed for the year 2026 and beyond. In this role, you will define the technical roadmap for our most ambitious projects, bridging the gap between cutting-edge research and scalable production engineering.
We are looking for a thought leader who is passionate about the convergence of generative AI, autonomous agents, and ethical machine learning. If you thrive in a fast-paced, innovative environment and want to shape the technology that will define the next decade, apply today.
Responsibilities
- Architect Scalable Systems: Design and implement robust, high-availability machine learning infrastructure capable of handling billions of inference requests.
- Lead Research Implementation: Translate theoretical AI research into practical, deployable solutions focusing on Large Language Models (LLMs) and multimodal systems.
- Define 2026 Roadmap: Create a long-term technical strategy that aligns with the company's vision for the future, identifying emerging technologies and integration points.
- Optimize Performance: Continuously monitor and improve model latency, accuracy, and cost-efficiency through rigorous A/B testing and optimization.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering teams to deliver features that delight users.
- Mentorship: Guide and mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: Minimum of 5-7 years of professional experience in software engineering and machine learning architecture.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and modern MLOps tools (Kubernetes, MLflow, Docker).
- AI Expertise: Proven track record of working with Deep Learning architectures, NLP, Computer Vision, or Reinforcement Learning.
- Problem Solving: Strong ability to deconstruct complex problems and design elegant, scalable technical solutions.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.