Job Description
We are entering a new era of technological evolution, and Nexus Horizon Labs is at the forefront of defining the Artificial General Intelligence (AGI) landscape for the year 2026. We are seeking a visionary and technically rigorous AI Research Scientist to lead our next-generation research initiatives. If you are passionate about pushing the boundaries of what machines can learn, reason, and create, this is your opportunity to shape the future.
In this role, you will work within a high-performance team dedicated to solving the most complex problems in machine learning, neural architecture search, and cognitive computing. We offer a competitive compensation package, equity packages, and the chance to work on projects that will define the next decade of human-machine interaction.
Responsibilities
- Architect Next-Gen Models: Design and implement cutting-edge deep learning architectures capable of achieving human-level reasoning by 2026.
- Research Leadership: Lead internal research projects focused on Large Language Models (LLMs), Reinforcement Learning, and Multimodal AI.
- Collaboration: Partner with cross-functional engineering and product teams to translate theoretical research into scalable production systems.
- Ethical AI: Establish and enforce rigorous ethical guidelines and safety protocols for autonomous AI agents.
- Publishing: Contribute to top-tier academic conferences and publish breakthrough papers in the field of AI.
- Code Optimization: Optimize training pipelines for efficiency, reducing computational costs while increasing model accuracy.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: Minimum 5 years of experience in AI research, deep learning, or a related technical role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed training frameworks.
- Mathematical Maturity: Strong foundation in linear algebra, calculus, probability, and statistics.
- Problem Solving: Demonstrated ability to tackle ambiguous, open-ended research problems with innovative solutions.
- Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to diverse audiences.