Job Description
Nexus Horizon Solutions is on a mission to define the technological landscape of 2026 and beyond. We are seeking a visionary AI & Machine Learning Architect to lead our advanced research division. In this pivotal role, you will not just build models; you will architect the future of intelligent systems, ensuring our solutions are scalable, ethical, and revolutionary.
We are looking for a pioneer who thrives in ambiguity and possesses the technical prowess to turn abstract concepts into tangible, high-impact products. If you are ready to shape the next generation of artificial intelligence, we want to hear from you.
Responsibilities
- Architect Future-Proof Systems: Lead the design and deployment of next-generation Large Language Models (LLMs) and predictive algorithms tailored for 2026 market demands.
- Strategic Integration: Collaborate with cross-functional teams to seamlessly integrate AI solutions into core business products and infrastructure.
- Best Practices & Governance: Establish rigorous best practices for data governance, model explainability, and ethical AI usage.
- Research & Innovation: Conduct deep research into emerging AI paradigms, including Generative AI and Reinforcement Learning, to stay ahead of the curve.
- Lifecycle Management: Oversee the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model training and production monitoring.
- Talent Development: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Statistics, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: Proven experience (5+ years) in developing production-grade machine learning systems, preferably in a high-growth tech environment.
- Technical Stack: Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Domain Expertise: Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Cloud Mastery: Strong grasp of cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Soft Skills: Exceptional problem-solving abilities, strategic thinking, and the ability to communicate complex technical concepts to non-technical stakeholders.