Job Description
Are you ready to define the future of Artificial Intelligence?
Nexus Future Systems is pioneering the next generation of intelligent systems. We are looking for a visionary Senior AI Architect to lead our research and development in predictive modeling, generative AI, and autonomous systems. This is not just a job; it is a mission to architect the technological landscape of 2026 and beyond.
In this role, you will bridge the gap between theoretical machine learning and scalable production systems. You will lead a team of elite engineers, optimize complex algorithms, and ensure our AI solutions are robust, ethical, and transformative.
Why Join Us?
- Impact: Work on projects that redefine human-computer interaction.
- Flexibility: Hybrid work model supporting innovation anywhere.
- Equity: Competitive stock options in a high-growth unicorn.
If you are a thought leader passionate about the future of tech, we want to hear from you.
Responsibilities
- Design and architect scalable, high-performance AI and machine learning systems for enterprise applications.
- Lead the end-to-end development lifecycle of NLP, Computer Vision, and Predictive Analytics models.
- Collaborate with cross-functional teams of data scientists, software engineers, and product managers to translate business requirements into technical specifications.
- Mentor junior engineers and architects, fostering a culture of continuous learning and technical excellence.
- Stay at the forefront of AI research, evaluating new frameworks (e.g., LLMs, Transformers) and integrating them into our tech stack.
- Ensure data integrity, model robustness, and ethical AI practices across all projects.
- Drive technical strategy for infrastructure optimization, reducing latency and improving inference speeds.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field (10+ years of experience).
- Proven expertise in designing and deploying production-grade AI systems at scale.
- Strong proficiency in Python, TensorFlow, PyTorch, and modern cloud infrastructure (AWS/GCP/Azure).
- Deep understanding of MLOps, CI/CD pipelines, and containerization technologies (Docker/Kubernetes).
- Experience with Large Language Models (LLMs), Generative AI, and Reinforcement Learning.
- Excellent problem-solving skills with a focus on architectural scalability and fault tolerance.
- Strong communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.