Job Description
Shape the Future of Intelligence in 2026
Nexus Future Labs is pioneering the next generation of Artificial General Intelligence. We are seeking a visionary Senior AI Research Engineer to join our elite team in San Francisco. As we gear up for the transformative year of 2026, you will be at the forefront of developing scalable, autonomous AI systems designed to revolutionize industries.
Our mission is to engineer the impossible. You won't just be maintaining legacy systems; you will be building the core architecture that powers our predictive models, multimodal agents, and future-proof technology stack. If you are passionate about the convergence of deep learning, neural architecture search, and ethical AI, we want to meet you.
Why Nexus Future Labs?
- Next-Gen Technology: Work with the latest frameworks and cutting-edge research.
- Impactful Work: Your code will define the AI landscape for 2026 and beyond.
- Competitive Compensation: Top-tier salary and equity packages for top-tier talent.
- Remote-First Culture: Flexible work arrangements with a collaborative office in SF.
Responsibilities
- Lead the design and implementation of novel neural network architectures for large-scale AI applications.
- Conduct cutting-edge research in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Optimize existing models for speed, accuracy, and efficiency in production environments.
- Collaborate with cross-functional teams to translate research findings into scalable software solutions.
- Stay ahead of industry trends and contribute to the company's 2026 strategic roadmap.
- Mentor junior engineers and researchers, fostering a culture of innovation and technical excellence.
Qualifications
- PhD or MS in Computer Science, Artificial Intelligence, or a related technical field.
- 5+ years of professional experience in Machine Learning or AI research roles.
- Deep proficiency in Python, PyTorch, and TensorFlow.
- Strong background in LLM fine-tuning, RAG architectures, and vector databases.
- Experience deploying AI models to cloud environments (AWS, GCP, or Azure).
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.