Job Description
Are you ready to architect the technological landscape of 2026?
Nexus Horizon Systems is seeking a visionary Senior AI & Machine Learning Architect to lead our mission in building the autonomous, intelligent systems of tomorrow. As we prepare for the technological paradigm shift expected in 2026, we need a leader who can bridge the gap between current generative AI and the next generation of autonomous agents.
In this role, you won't just maintain legacy systems; you will design, deploy, and scale the core infrastructure that powers our next-gen consumer products. We are looking for a forward-thinker who understands the ethical implications of AGI and can build scalable, resilient models for a global audience.
Why Join Nexus Horizon?
- Shape the future of technology alongside industry pioneers.
- Competitive compensation package reflecting your expertise.
- Access to cutting-edge compute resources and R&D freedom.
- Work on projects that define the standards for 2026 and beyond.
Responsibilities
- Design and implement scalable machine learning pipelines and infrastructure optimized for the 2026 data landscape.
- Lead the research and development of Generative AI models, focusing on hallucination reduction and context retention.
- Collaborate with cross-functional teams (Product, Engineering, Ethics) to integrate AI into user-facing products seamlessly.
- Mentor junior data scientists and engineers, fostering a culture of continuous learning and innovation.
- Ensure system scalability, security, and compliance with emerging global AI regulations.
- Predict and prepare for emerging AI trends, specifically those expected to disrupt the market in 2026.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- 7+ years of professional experience in machine learning, deep learning, or data science.
- Proven expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks.
- Deep understanding of Large Language Models (LLMs), RAG architectures, and prompt engineering.
- Experience deploying AI models to production environments (AWS, GCP, or Azure).
- Strong grasp of software engineering best practices, including CI/CD and version control.