Job Description
Are you ready to shape the technological landscape of 2026 and beyond?
Nexus Future Labs is seeking a visionary AI Systems Architect to lead our next-generation infrastructure projects. In this role, you won't just implement existing solutions; you will architect the systems that will define the future of work, autonomous decision-making, and human-AI collaboration.
We are looking for a self-starter who thrives in ambiguity and has a passion for solving complex, unsolved problems.
Why join us?
- Work at the intersection of cutting-edge AI and enterprise scalability.
- Shape the roadmap for the future of automation.
- Competitive compensation and equity package.
Responsibilities
- Architect Scalable Systems: Design and build high-performance AI infrastructures tailored for the enterprise of 2026, focusing on latency, throughput, and reliability.
- MLOps Leadership: Lead the design and implementation of end-to-end MLOps pipelines, ensuring seamless model training, deployment, and monitoring.
- Cross-Functional Innovation: Collaborate with product managers, data scientists, and engineers to integrate advanced AI capabilities (LLMs, predictive analytics) into core business workflows.
- Ethical AI Governance: Define and enforce ethical guidelines and governance frameworks for AI usage to ensure compliance and fairness.
- Emerging Tech Prototyping: Research and prototype emerging technologies to stay ahead of industry trends and maintain a competitive edge.
Qualifications
- Education: Master’s degree in Computer Science, Engineering, Mathematics, or a related field (PhD preferred).
- Experience: 5+ years of experience in Machine Learning, Deep Learning, or Systems Architecture, with at least 2 years in a lead or architect role.
- Technical Skills: Expert proficiency in Python, TensorFlow, PyTorch, and cloud platforms (AWS, GCP, or Azure).
- Infrastructure: Strong understanding of MLOps, Kubernetes, Docker, and distributed systems.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts to non-technical stakeholders.