Job Description
Architect the Intelligence of Tomorrow.
At Nexus Future Systems, we are not merely building software; we are engineering the foundation of the next technological revolution. We are seeking a visionary Senior AI Architect to spearhead our research into advanced Large Language Models (LLMs) and autonomous agents. Our mission is to prepare for the year 2026 by solving today's most complex data challenges.
As a key member of our elite R&D team, you will have the autonomy to define technical roadmaps and the resources to build systems that define the standard for the industry. We value deep expertise, creative problem-solving, and a passion for the ethical advancement of artificial intelligence.
Why Join Us?
- Work on state-of-the-art Generative AI projects that scale to millions of users.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first culture with hubs in San Francisco and New York.
- Access to the latest hardware for model training and inference.
Responsibilities
- Model Development: Design, train, and fine-tune proprietary LLMs, focusing on reasoning capabilities, hallucination reduction, and context retention.
- Infrastructure Architecture: Build scalable MLOps pipelines and distributed computing systems capable of processing petabytes of data efficiently.
- Research Leadership: Stay ahead of the curve by integrating cutting-edge research from top conferences (NeurIPS, ICML) into production systems.
- Cross-Functional Collaboration: Partner with product and engineering teams to translate complex AI concepts into user-friendly, high-impact applications.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Ethical AI: Establish and enforce guidelines for bias detection, data privacy, and responsible AI deployment.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in machine learning engineering, applied AI research, or a similar senior technical role.
- Technical Stack: Deep proficiency in Python, PyTorch, or TensorFlow. Experience with LangChain and Hugging Face is highly preferred.
- Domain Knowledge: Extensive knowledge of Natural Language Processing (NLP), Transformers, and Reinforcement Learning from Human Feedback (RLHF).
- Systems: Strong understanding of distributed systems, cloud architecture (AWS/GCP), and Kubernetes.
- Communication: Exceptional ability to communicate complex technical ideas to non-technical stakeholders and leadership.