Job Description
Welcome to the future of technology. At Nexus Future, we are not just predicting the advancements of 2026; we are actively engineering them. We are looking for a visionary Senior AI Research Scientist to join our elite team in San Francisco and lead the charge in developing next-generation generative models and autonomous systems.
If you are passionate about pushing the boundaries of Machine Learning, Deep Learning, and Neural Networks, and you want to work in an environment that fosters radical innovation, we want to hear from you. This is an opportunity to define the technical roadmap for a company built on the promise of the future.
Responsibilities
- Lead Research Initiatives: Spearhead the design and execution of advanced AI research projects focused on Large Language Models (LLMs), computer vision, and predictive analytics.
- Model Optimization: Develop and optimize deep learning architectures to improve inference speed, accuracy, and scalability for real-world applications.
- Technical Strategy: Collaborate with cross-functional engineering teams to translate complex research concepts into production-ready software and scalable infrastructure.
- Publish & Present: Author high-impact research papers and present findings at top-tier AI conferences to establish our thought leadership in the industry.
- Code Review & Mentorship: Provide technical leadership by reviewing code, conducting code reviews, and mentoring junior data scientists and researchers.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
- Technical Expertise: Deep understanding of machine learning algorithms, statistical methods, and software engineering best practices.
- Programming: Proficiency in Python, with extensive experience using frameworks such as PyTorch, TensorFlow, or JAX.
- Experience: 5+ years of professional experience in AI research or a related role within a high-tech environment.
- Problem Solving: Demonstrated ability to tackle unstructured problems and derive insights from complex datasets.