Job Description
Join Nexus Future Labs, a pioneering force in artificial intelligence, as our next Generative AI Research Scientist. We are on a mission to build the cognitive infrastructure for the year 2026 and beyond. In this role, you will push the boundaries of Large Language Models (LLMs), multimodal architectures, and safe AGI alignment. You will work in a high-performance environment where innovation is not just encouraged—it is the standard.
Why Join Us?
- Impact at Scale: Your research will directly power the next generation of enterprise AI solutions.
- Top-Tier Talent: Collaborate with world-class engineers, data scientists, and ethical AI researchers.
- Future-Ready: Work on cutting-edge problems that define the technological landscape of 2026 and beyond.
If you are passionate about the ethical development of AI and want to shape the future of human-computer interaction, we want to hear from you.
Responsibilities
- Design and implement state-of-the-art algorithms for training and fine-tuning large-scale generative models.
- Evaluate model performance, safety, and alignment with human values to ensure robust deployment.
- Conduct rigorous A/B testing and benchmarking against current industry standards (e.g., GPT-4, Claude, Llama).
- Collaborate with product teams to translate complex research findings into scalable, production-ready features.
- Stay ahead of the curve by monitoring emerging research in the AI community and patenting novel methodologies.
- Write and publish high-impact research papers to contribute to the global AI knowledge base.
Qualifications
- Education: PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Technical Skills: Deep expertise in Python, PyTorch, or TensorFlow. Experience with Hugging Face Transformers and LangChain.
- Experience: 5+ years of experience in machine learning research or software engineering focused on NLP.
- Knowledge: Solid understanding of Deep Learning architectures, Transformers, Attention mechanisms, and Generative Adversarial Networks (GANs).
- Tools: Proficiency in version control (Git), Docker, and cloud platforms (AWS/GCP/Azure).
- Soft Skills: Excellent communication skills with the ability to articulate complex technical concepts to diverse stakeholders.