Job Description
We are not just building software for today; we are architecting the intelligent infrastructure of 2026. At Nebula Core Systems, we are at the intersection of Generative AI, Autonomous Agents, and Predictive Analytics. We are seeking a visionary Senior AI Research Engineer to lead our R&D division in defining the next generation of human-machine collaboration.
In this role, you will move beyond traditional coding to push the boundaries of what artificial intelligence can achieve. You will build the models that will power our products a decade from now, ensuring our technology remains future-proof and ahead of the curve.
Responsibilities
- Architect Future-Proof Models: Design and implement advanced deep learning architectures capable of reasoning, adaptation, and complex task execution in 2026 and beyond.
- Lead Research Initiatives: Spearhead R&D projects focusing on Multimodal Learning, Large Language Models (LLMs), and Reinforcement Learning from Human Feedback (RLHF).
- Optimize Inference Pipelines: Engineer high-throughput, low-latency systems capable of handling billions of tokens efficiently.
- Collaborate on Next-Gen Products: Work closely with product and engineering teams to integrate cutting-edge AI capabilities into consumer and enterprise solutions.
- Establish Technical Standards: Define best practices for model training, evaluation, and deployment within the organization.
- Mentor High-Performance Teams: Guide a team of talented data scientists and ML engineers in their technical growth and career development.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field with a focus on AI.
- Experience: 5+ years of professional experience in Deep Learning, Natural Language Processing, or Computer Vision.
- Technical Proficiency: Expert-level proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Architecture Knowledge: Deep understanding of Transformer models, attention mechanisms, and distributed training strategies.
- Problem Solving: Demonstrated ability to tackle open-ended, ambiguous problems and deliver scalable solutions.
- Innovation: A track record of publishing in top-tier AI conferences (NeurIPS, ICML, ICLR) or delivering significant industry breakthroughs.