Job Description
Nexus Horizon Solutions is pioneering the next generation of intelligent systems. We are seeking a visionary Senior AI Architect to lead our machine learning infrastructure and drive innovation in predictive analytics and generative AI. This role is critical as we scale our platform to support enterprise clients worldwide and shape the technological landscape for 2026 and beyond.
In this position, you will bridge the gap between theoretical research and production-grade engineering, ensuring our AI models are robust, scalable, and ethically sound. You will define the technical vision for our AI stack and mentor the next generation of engineering talent.
Responsibilities
- System Architecture: Design and implement scalable, high-performance machine learning pipelines and data architectures using modern cloud-native technologies.
- Model Development: Lead the research, development, and fine-tuning of advanced AI models, including Large Language Models (LLMs) and deep learning frameworks.
- MLOps Strategy: Establish and maintain CI/CD pipelines for ML, ensuring reproducibility and deployment efficiency using tools like Docker, Kubernetes, and Airflow.
- Team Leadership: Mentor a team of data scientists and ML engineers, conducting code reviews and fostering a culture of technical excellence and continuous learning.
- Stakeholder Collaboration: Work closely with product managers and business stakeholders to translate complex AI capabilities into tangible business value and user-centric solutions.
- Roadmap Planning: Define the long-term technical roadmap for AI initiatives, evaluating emerging technologies to keep Nexus Horizon at the forefront of innovation.
Qualifications
- Experience: 5+ years of experience in software engineering or machine learning, with at least 3 years in a senior architectural or lead role.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or scikit-learn; strong SQL and NoSQL database skills.
- Cloud Computing: Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or a related technical field.
- Soft Skills: Exceptional communication skills with the ability to explain complex technical concepts to non-technical stakeholders and cross-functional teams.
- Problem Solving: Demonstrated ability to solve complex technical challenges and optimize system performance under pressure.