Job Description
Join Nexus Horizon Technologies as we pioneer the next generation of artificial intelligence. We are seeking a visionary Senior AI Research Engineer to lead the development of our flagship 'Project 2026' initiative—a transformative suite of autonomous agents designed to redefine human-machine collaboration.
In this role, you will not just build models; you will architect the future. You will work with cutting-edge Large Language Models (LLMs), multimodal architectures, and reinforcement learning frameworks to solve complex, unsolved problems. If you are passionate about pushing the boundaries of what is possible in 2026 and beyond, we want to hear from you.
Why Join Us?
- Impactful Work: Directly contribute to technology that will shape the next decade of enterprise automation.
- Top-Tier Talent: Collaborate with PhD-level researchers and industry veterans.
- Future-Ready: Work in a dynamic environment focused on long-term R&D and scalability.
Are you ready to build the AI of tomorrow, today?
Responsibilities
- Lead the architectural design and implementation of proprietary AI models for the Project 2026 initiative.
- Conduct advanced research in Natural Language Processing (NLP), Computer Vision, and Generative AI to enhance model accuracy and efficiency.
- Optimize existing neural networks for low-latency inference and high-throughput deployment in production environments.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate research into scalable software solutions.
- Stay at the forefront of AI advancements, evaluating new technologies (e.g., Transformers, Diffusion Models) and integrating them into our tech stack.
- Mentor junior engineers and researchers, fostering a culture of innovation and continuous learning.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Minimum of 5+ years of professional experience in AI/ML research or software engineering.
- Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Strong understanding of deep learning principles, MLOps pipelines, and distributed training systems.
- Experience with model fine-tuning, RLHF, and deploying LLMs on cloud infrastructure (AWS/GCP/Azure).
- Excellent problem-solving skills and the ability to work independently in a fast-paced, innovative environment.