Job Description
Are you ready to architect the intelligence that will define the year 2026? At Nexus Future Systems, we are on a mission to push the boundaries of Artificial General Intelligence (AGI). We are seeking a visionary Senior AI Research Scientist to lead our cutting-edge research division in San Francisco. In this pivotal role, you will not just use existing models; you will build the foundational architectures for the next generation of autonomous systems.
Join a team of elite engineers, data scientists, and futurists dedicated to solving the world's most complex problems through advanced machine learning. We offer competitive compensation, equity packages, and a culture that prioritizes innovation over convention.
Responsibilities
- Spearhead R&D initiatives focused on Generative AI, Reinforcement Learning, and Neural Architecture Search for the 2026 roadmap.
- Design and implement scalable machine learning pipelines capable of processing petabytes of real-time data.
- Collaborate cross-functionally with product and engineering teams to translate theoretical research into deployable products.
- Mentor junior researchers and Ph.D. candidates, fostering a culture of academic excellence and practical application.
- Publish high-impact research papers in top-tier conferences (NeurIPS, ICML, ICLR) and contribute to open-source communities.
- Ensure ethical AI practices and data governance across all research projects.
- Identify emerging technologies and methodologies to maintain our competitive edge in the AI landscape.
Qualifications
- Ph.D. in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Minimum of 5+ years of experience in applied machine learning research or a comparable senior engineering role.
- Extensive proficiency in Python, PyTorch, and TensorFlow.
- Strong background in Deep Learning, Natural Language Processing (NLP), or Computer Vision.
- Proven track record of leading complex research projects from conception to deployment.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Kafka).