Job Description
We are on the cusp of a technological revolution, and Nexus Horizon is leading the charge into the future. We are seeking a visionary Next-Gen AI/ML Architect to design the foundational intelligence systems for the year 2026 and beyond. You will be at the intersection of advanced deep learning, autonomous agents, and scalable cloud infrastructure.
In this role, you will not just build models; you will architect the cognitive architecture of tomorrow. You will work with a world-class team of researchers and engineers to push the boundaries of what is possible in Generative AI, Large Language Models (LLMs), and ethical AI alignment.
Why Nexus Horizon?
• Competitive equity package
• Flexible remote-first culture
• Access to cutting-edge compute resources
• Impact on the future of human-AI collaboration
Responsibilities
- Architect Next-Gen Models: Design and implement scalable AI architectures that support autonomous decision-making and advanced predictive analytics for 2026-era applications.
- Research Leadership: Spearhead research initiatives in Generative AI, specifically focusing on multimodal models and ethical AI alignment.
- Infrastructure Optimization: Build high-throughput, low-latency inference pipelines and optimize training clusters for large-scale distributed training.
- Collaboration & Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence across the organization.
- Roadmap Strategy: Define the technical roadmap for AI capabilities, ensuring alignment with business goals and future technological trends.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related technical field, with a focus on Artificial Intelligence or Machine Learning.
- Experience: 5+ years of professional experience in building and deploying production-level Machine Learning systems.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Experience with distributed training frameworks (Ray, Spark MLlib).
- Domain Knowledge: Proven track record in NLP, Computer Vision, or Reinforcement Learning. Experience with LLMs (GPT, LLaMA, Claude) is highly desirable.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems with elegant, scalable solutions.