Job Description
The Future is Here. Are You Building It?
Nexus Horizon AI is at the forefront of the 2026 technological revolution. We are looking for a visionary Senior AI/ML Engineer to lead our next-generation Generative AI and Agentic workflow initiatives. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and want to architect the intelligence of tomorrow, we want to meet you.
In this pivotal role, you won't just be maintaining models; you will be defining the architecture for autonomous systems that will power enterprise solutions in the 2026 era. Join a team of elite engineers and researchers dedicated to ethical, scalable, and high-performance artificial intelligence.
Why Join Nexus Horizon AI?
- Competitive Salary: $180k - $260k base + Equity
- Comprehensive Benefits: Health, Dental, Vision, 401k Match
- Flexible Work: Hybrid model in the heart of San Francisco.
- Cutting-Edge Tech: Work with the latest in PyTorch, TensorFlow, and Quantum-ready frameworks.
Responsibilities
- Architect LLM Solutions: Design and deploy scalable Large Language Model pipelines optimized for high-throughput inference and low-latency responses.
- Research & Development: Lead R&D efforts in emerging AI paradigms relevant to the 2026 landscape, including multi-modal agents and memory-augmented reasoning.
- Model Optimization: Implement quantization, pruning, and distillation techniques to reduce computational costs while maintaining model accuracy.
- Production Deployment: Manage the full ML lifecycle from prototype to production using CI/CD pipelines and containerization (Docker, Kubernetes).
- Collaboration: Partner with cross-functional teams (Product, Data Science, UX) to translate complex business requirements into robust technical solutions.
- Code Review & Mentorship: Conduct rigorous code reviews and mentor junior engineers to maintain high engineering standards.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field; PhD preferred.
- Experience: 5+ years of professional experience in Machine Learning and Deep Learning.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; hands-on experience with Hugging Face Transformers and LangChain.
- Infrastructure: Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and MLOps best practices.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems and optimize algorithmic performance.
- Communication: Excellent verbal and written communication skills, capable of explaining technical concepts to non-technical stakeholders.