Job Description
Are you ready to architect the next generation of artificial intelligence? Nexus Horizon AI is seeking a visionary Senior AI Research Engineer to lead our strategic initiatives for the 2026 product roadmap. In this pivotal role, you will be at the forefront of developing scalable, multimodal Large Language Models (LLMs) that will define the future of human-computer interaction.
We are not just building software; we are defining the technological landscape for the year 2026 and beyond. You will work in a high-performance environment, pushing the boundaries of what is possible in generative AI, ethical reasoning, and autonomous agent systems.
Responsibilities
- Lead Model Architecture: Design and implement scalable neural network architectures capable of processing complex, multi-modal data streams for the 2026 release cycle.
- Optimization & Efficiency: Utilize techniques such as quantization and pruning to deploy large-scale models on edge devices without compromising performance.
- Research & Development: Stay ahead of the curve by integrating cutting-edge research from top conferences (NeurIPS, ICML) into our production pipelines.
- Cross-Functional Collaboration: Partner with product managers and engineers to translate technical roadmaps into deployable, high-impact software solutions.
- Ethical AI Governance: Establish and enforce strict guidelines for bias mitigation and safety in generative outputs to ensure responsible AI deployment.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence or Machine Learning.
- Technical Expertise: Proven experience building and deploying production-ready LLMs or Transformers using frameworks like PyTorch or TensorFlow.
- Programming: Deep proficiency in Python and C++ with a strong understanding of GPU compute optimization.
- Experience: Minimum of 5 years of experience in a senior engineering or research role within the AI/ML space.
- Problem Solving: Demonstrated ability to tackle complex, ambiguous problems with innovative, data-driven solutions.