Job Description
We are seeking a visionary Senior Generative AI Architect to lead the next generation of intelligent systems at Nexus Future Systems. As we push the boundaries of what is possible in 2026 and beyond, you will be at the forefront of developing scalable, safe, and impactful large language models (LLMs).
In this role, you will bridge the gap between cutting-edge research and production-grade engineering, designing architectures that define the future of human-computer interaction. If you are passionate about the ethical implications of AI and possess the technical prowess to build systems that matter, we want to hear from you.
Responsibilities
- Architect LLM Infrastructure: Design and deploy scalable, high-performance generative AI pipelines from scratch, utilizing state-of-the-art transformer architectures.
- Optimization & Performance: Implement model quantization, pruning, and distributed inference strategies to reduce latency and operational costs.
- R&D Leadership: Lead a team of ML engineers and researchers in exploring novel techniques in RLHF (Reinforcement Learning from Human Feedback) and fine-tuning.
- System Integration: Collaborate closely with product and engineering teams to integrate generative AI capabilities seamlessly into consumer and enterprise applications.
- Policy & Safety: Define and implement guardrails and safety protocols to ensure AI outputs are aligned with ethical standards and regulatory requirements.
Qualifications
- Education: M.S. or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 4 years focused specifically on Machine Learning and Deep Learning.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and C++.
- Domain Knowledge: Extensive experience with NLP, LLMs, GANs, or Diffusion models; familiarity with RAG (Retrieval-Augmented Generation) architectures.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts for diverse stakeholders.