Job Description
Are you ready to architect the intelligence of tomorrow? Nexus Horizon is seeking a visionary Senior AI Research Scientist to lead our cutting-edge initiatives for the 2026 roadmap. We are not just building software; we are defining the future of human-computer interaction through advanced machine learning and generative AI.
In this pivotal role, you will spearhead the development of next-generation algorithms that will power our platform for years to come. You will work in a collaborative, high-performance environment alongside world-class engineers and product designers, pushing the boundaries of what is possible in artificial intelligence.
Why Join Nexus Horizon?
- Impactful Work: Directly influence the strategic direction of our 2026 technology stack.
- World-Class Team: Collaborate with industry leaders in AI, distributed systems, and cloud architecture.
- Competitive Package: Top-tier salary, equity, and comprehensive benefits.
If you are passionate about research, possess a deep understanding of neural networks, and want to build the infrastructure for the future, we want to hear from you.
Responsibilities
- Lead core research initiatives focused on LLMs, Natural Language Processing, and computer vision, directly contributing to our 2026 strategic goals.
- Design, develop, and deploy scalable machine learning models that integrate seamlessly into our production environment.
- Collaborate with cross-functional product teams to translate complex research findings into practical, user-centric features.
- Mentor junior data scientists and engineers, fostering a culture of innovation and continuous learning within the research division.
- Stay at the forefront of the industry by publishing papers, attending conferences, and exploring emerging technologies.
- Optimize existing models for speed, accuracy, and cost-efficiency in high-volume production systems.
Qualifications
- Ph.D. or Master's degree in Computer Science, Mathematics, or a related quantitative field with a focus on AI/ML.
- Minimum of 5 years of professional experience in applied machine learning research and development.
- Expert proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Strong background in distributed systems and large-scale data processing (e.g., Spark, Kubernetes).
- Proven track record of publishing research in top-tier conferences (NeurIPS, ICML, ACL) or open-source contributions.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.