Job Description
We are pioneering the next era of intelligence with our flagship Project 2026. As a Lead AI Architect, you will define the technical roadmap for our autonomous systems and predictive analytics platforms. You will work at the intersection of deep learning, edge computing, and scalable cloud infrastructure.
At Nexus Future Systems, we don't just build software; we engineer the future. If you are passionate about pushing the boundaries of what is possible in artificial intelligence and want to leave a legacy, this is your opportunity.
Why Join Us?
- Work on cutting-edge technology that defines the market landscape.
- Competitive equity package and top-tier healthcare benefits.
- Flexible remote and hybrid work policies.
- Access to state-of-the-art hardware and research facilities.
Responsibilities
- Architectural Leadership: Define and execute the technical vision for Project 2026, ensuring scalability, security, and performance.
- Model Development: Design and implement complex deep learning models and neural networks to solve enterprise-level challenges.
- Team Mentorship: Lead a high-performance team of data scientists and engineers, fostering a culture of innovation and continuous learning.
- Research & Innovation: Stay abreast of the latest AI trends and research papers to integrate breakthrough technologies into our production environment.
- System Integration: Oversee the integration of AI models into our existing microservices architecture.
- Stakeholder Communication: Translate complex technical concepts into actionable insights for non-technical stakeholders and investors.
Qualifications
- Education: Master’s degree in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- Experience: 7+ years of experience in software engineering, with at least 3 years in a lead architectural role.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
- Cloud Expertise: Strong experience with AWS, Azure, or GCP, specifically in deploying machine learning pipelines.
- Problem Solving: Proven track record of solving complex, ambiguous problems in high-pressure environments.
- Communication: Excellent verbal and written communication skills with the ability to present to diverse audiences.