Job Description
Join the Future of Intelligence. Nexus Intelligence is pioneering the next generation of Large Language Models and Autonomous Agents. We are seeking a visionary Senior AI Research Engineer to lead the development of cutting-edge algorithms that will redefine human-machine interaction.
We are looking for individuals who are not just familiar with the state-of-the-art, but are capable of pushing the boundaries of what is possible. You will work in a collaborative, high-performance environment alongside world-class researchers and engineers.
Why Join Us?
- Work on groundbreaking projects with a competitive compensation package.
- Access to state-of-the-art compute resources and proprietary datasets.
- Flexible remote-first culture with a focus on work-life balance.
- Opportunity to publish in top-tier conferences (NeurIPS, ICML, ACL).
Apply today to shape the future of AI.
Responsibilities
- Research & Development: Design, implement, and optimize deep learning models, focusing on Natural Language Processing (NLP) and Computer Vision.
- Model Engineering: Train, fine-tune, and deploy large-scale transformer models ensuring high accuracy and low latency.
- Performance Optimization: Conduct rigorous benchmarking and optimization to improve inference speeds and reduce computational costs.
- Cross-functional Collaboration: Partner with product and engineering teams to translate research findings into scalable, production-ready software solutions.
- Documentation: Produce high-quality technical documentation, patents, and research papers to share your discoveries with the global AI community.
- Experimentation: Explore novel architectures and training methodologies to push the envelope of current AI capabilities.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.
- Experience: 5+ years of professional experience in applied machine learning or AI research.
- Technical Skills: Strong proficiency in Python, PyTorch, or TensorFlow. Deep understanding of neural network architectures.
- Mathematical Foundation: Solid grasp of linear algebra, calculus, probability, and optimization theory.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and derive innovative solutions.
- Communication: Excellent written and verbal communication skills, with a track record of publishing in top-tier conferences.