Job Description
Are you ready to architect the intelligence of tomorrow? Nexus Horizon Solutions is seeking a visionary Senior AI Research Scientist to lead our groundbreaking '2026 Horizon' initiative. We are not just building software; we are defining the trajectory of artificial general intelligence for the next decade. If you thrive on solving unsolved problems and pushing the boundaries of what is possible in machine learning, this is your opportunity to shape the future.
In this pivotal role, you will bridge the gap between theoretical research and practical application, working alongside a team of elite engineers and data scientists to deploy cutting-edge models that will define the 2026 technological landscape.
Responsibilities
- Lead the research and development of next-generation deep learning architectures focused on long-term forecasting and autonomous agent systems.
- Design and implement scalable algorithms capable of processing massive datasets in real-time to predict future market and technological trends.
- Collaborate with cross-functional teams to integrate advanced AI models into production environments, ensuring robustness and ethical compliance.
- Author high-impact research papers and patents that contribute to the open-source community and establish Nexus Horizon as a thought leader.
- Mentor junior researchers and data scientists, fostering a culture of innovation and continuous learning within the engineering department.
- Conduct rigorous testing and validation of AI systems to ensure accuracy, safety, and reliability in high-stakes environments.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
- Minimum of 5+ years of experience in research engineering, with a proven track record of publications in top-tier conferences (NeurIPS, ICML, ICLR).
- Expert proficiency in Python, PyTorch, TensorFlow, and modern MLOps tools.
- Deep understanding of Transformer models, Large Language Models (LLMs), and reinforcement learning methodologies.
- Strong problem-solving skills with the ability to tackle ambiguous, open-ended research problems.
- Demonstrated experience leading technical teams and managing complex research projects from ideation to deployment.