Job Description
We are on the brink of a technological renaissance, and Nexus Future Labs is leading the charge into 2026. We are seeking a visionary Senior AI Research Scientist to architect the next generation of autonomous systems and generative intelligence. In this pivotal role, you won't just use existing tools; you will define the algorithms that will power the digital ecosystem for the coming decade.
If you are passionate about pushing the boundaries of Machine Learning, Deep Learning, and Artificial General Intelligence (AGI), and you want to leave a lasting legacy in the tech world, we want to meet you.
Why Join Us?
- Work on cutting-edge projects that will shape the future of human-computer interaction.
- Competitive compensation package and equity options.
- Flexible remote-first culture with state-of-the-art facilities in San Francisco.
- Continuous learning budget and access to the world's best research papers and datasets.
Responsibilities
- Lead the research and development of novel AI architectures for the 2026 roadmap, focusing on scalability and efficiency.
- Design, train, and evaluate complex deep learning models using Python, TensorFlow, and PyTorch.
- Collaborate with cross-functional teams of engineers, product managers, and designers to translate research into deployable products.
- Publish high-impact research papers in top-tier AI conferences (NeurIPS, ICML, ICLR) and contribute to open-source communities.
- Mentor junior researchers and data scientists, fostering a culture of innovation and technical excellence.
- Stay ahead of the curve on emerging AI trends, including Large Language Models (LLMs) and reinforcement learning.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, or a related field with a focus on AI/ML.
- Minimum of 5 years of experience in research or applied machine learning roles.
- Strong proficiency in programming languages, specifically Python, C++, and SQL.
- Deep understanding of machine learning theory, including probabilistic models, optimization, and neural networks.
- Proven track record of delivering production-grade AI solutions.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.