Job Description
Join the Pioneers of Tomorrow.
Nexus Future Systems is at the forefront of the AI revolution. We are not just building applications; we are architecting the cognitive infrastructure of the year 2026 and beyond. We are looking for a visionary Senior AI Research Scientist to lead our Generative AI division.
In this role, you will push the boundaries of Large Language Models (LLMs), Computer Vision, and autonomous agent systems. You will work in a dynamic, high-performance environment where your research directly translates into products that redefine human-machine interaction. If you are passionate about the theoretical underpinnings of intelligence and the practical application of AI, this is your stage.
Why Nexus Future Systems?
- Impactful Work: Your models will power next-generation customer experiences and enterprise automation.
- Top-Tier Talent: Collaborate with PhDs, engineers, and designers from the world's leading tech institutions.
- Future-Ready Culture: We embrace the rapid pace of innovation, prioritizing agility and continuous learning.
Responsibilities
- Lead Research Initiatives: Spearhead the research and development of state-of-the-art generative models, focusing on scalability and efficiency.
- Model Optimization: Design and implement novel training pipelines and optimization techniques to improve model accuracy and reduce inference costs.
- Publication & Thought Leadership: Publish cutting-edge research in top-tier conferences (NeurIPS, ICML, ACL) and contribute to open-source communities.
- Technical Mentorship: Guide and mentor a team of junior researchers and data scientists, fostering a culture of technical excellence.
- Cross-Functional Collaboration: Partner with product managers and engineering teams to translate theoretical research into production-ready solutions.
- Algorithm Design: Architect robust algorithms capable of handling complex, real-world edge cases and diverse data inputs.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Machine Learning, Mathematics, or a related quantitative field.
- Experience: 5+ years of hands-on experience in Deep Learning, specifically with Neural Networks and NLP.
- Tech Stack: Proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Expertise: Strong background in Transformers, Attention Mechanisms, and Reinforcement Learning.
- Coding Standards: Demonstrated ability to write clean, maintainable, and efficient code.
- Communication: Excellent written and verbal communication skills with the ability to explain complex technical concepts to diverse stakeholders.
- Passion: A deep curiosity for the future of AI and a drive to solve unsolved problems.