Job Description
Are you ready to architect the technology of 2026 and beyond? Nexus Future Systems is seeking a visionary Senior AI Research Scientist to lead our breakthrough Generative AI division. In this pivotal role, you will define the research roadmap for next-generation Large Language Models (LLMs) and multimodal systems that will define the future of human-machine interaction. If you thrive in a fast-paced, high-impact environment and possess an insatiable curiosity for artificial general intelligence, we want to meet you.
As a key leader in our R&D team, you will bridge the gap between theoretical machine learning and scalable production engineering, ensuring our AI solutions are not only cutting-edge but also safe, efficient, and ethically aligned.
Responsibilities
- Lead R&D Initiatives: Spearhead research into state-of-the-art generative architectures, including Transformers, Diffusion models, and Reinforcement Learning from Human Feedback (RLHF).
- Model Development: Design, train, and optimize large-scale language models to achieve superior performance in reasoning, coding, and creative generation tasks.
- Technical Strategy: Collaborate with engineering leadership to define the technical roadmap and infrastructure requirements for deploying AI at scale.
- Cross-Functional Collaboration: Partner with product teams to translate complex AI capabilities into intuitive user experiences and commercial applications.
- Publication & Thought Leadership: Contribute to top-tier academic conferences and industry publications to establish Nexus Future Systems as a pioneer in the AI space.
- Code Review & Mentorship: Mentor junior researchers and engineers, conducting rigorous code reviews to maintain high standards of software engineering and data integrity.
Qualifications
- Education: Ph.D. or M.S. in Computer Science, Artificial Intelligence, Mathematics, or a related field with a focus on Deep Learning.
- Experience: 5+ years of professional experience in research or software engineering, with a proven track record of publications in top-tier venues (NeurIPS, ICML, ACL, etc.).
- Technical Skills: Expert proficiency in Python, PyTorch, or TensorFlow. Deep understanding of natural language processing (NLP) and machine learning theory.
- Problem Solving: Demonstrated ability to tackle unsolved problems in AI, including model interpretability, hallucination reduction, and efficiency optimization.
- Leadership: Strong communication skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
- Tools: Experience with distributed training systems (e.g., Ray, Kubernetes) and cloud platforms (AWS, GCP, Azure).