Job Description
Are you ready to architect the future of intelligence? Nexus Horizon is seeking a visionary Senior 2026 AI & Machine Learning Engineer to lead our advanced R&D initiatives. In this pivotal role, you will define the algorithms and architectures that will power the technological landscape of 2026 and beyond.
We are looking for a technical thought leader who thrives on ambiguity and innovation. You will work at the intersection of theoretical research and practical deployment, pushing the boundaries of what is possible in Generative AI, Large Language Models (LLMs), and next-generation neural architectures. You will not just build models; you will engineer the very fabric of future machine intelligence.
Why Join Nexus Horizon?
- Impactful Work: Directly contribute to the AI models that will define the next decade of human-computer interaction.
- Future-Forward Environment: Work with a team dedicated to '2026-ready' technology stacks and infrastructure.
- Competitive Compensation: Top-tier salary and equity package for industry leaders.
- Flexible Culture: Remote-first policy with hubs in San Francisco and Austin.
Responsibilities
- Architect 2026-Ready Models: Design, train, and fine-tune large-scale Generative AI and LLM architectures optimized for high-speed inference and energy efficiency.
- Research & Development: Conduct cutting-edge research in Deep Learning, Reinforcement Learning, and Quantum AI integration to solve complex industry problems.
- System Optimization: Engineer scalable data pipelines and deployment strategies that ensure model reliability and performance under real-world constraints.
- Collaborative Innovation: Partner with cross-functional teams of data scientists, engineers, and product managers to translate theoretical research into production-ready features.
- Mentorship: Guide junior engineers and researchers, fostering a culture of continuous learning and technical excellence within the AI division.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Artificial Intelligence research.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with Hugging Face Transformers, LangChain, or similar LLM frameworks is highly preferred.
- Mathematical Proficiency: Strong foundation in Linear Algebra, Calculus, Probability, and Statistics.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and innovate solutions in ambiguous environments.