Job Description
The Future Awaits at Nexus Future Labs
We are at the forefront of innovation, building the infrastructure for the year 2026 and beyond. As a Senior AI Research Scientist on our 2026 Horizon initiative, you will play a pivotal role in defining the next generation of artificial intelligence. We are looking for a visionary engineer who is passionate about pushing the boundaries of what is possible in Machine Learning and Deep Learning.
In this role, you will lead high-impact research projects aimed at solving complex, real-world problems. You will work in a dynamic environment that values creativity, technical excellence, and the rapid prototyping of breakthrough technologies.
Why Join Us?
- Work on cutting-edge projects that will define the technology landscape of 2026.
- Competitive compensation package with performance bonuses.
- Flexible work hours and a fully remote-first culture with access to premium NYC tech hubs.
- Access to state-of-the-art hardware and computing resources.
Responsibilities
- Lead the design and implementation of advanced AI models, specifically focusing on Generative AI and Reinforcement Learning for the 2026 strategic roadmap.
- Collaborate with product managers and engineers to translate research findings into scalable, production-ready software solutions.
- Conduct rigorous experimentation and statistical analysis to validate model performance and improve accuracy.
- Optimize existing neural network architectures for speed, efficiency, and reduced computational cost.
- Stay abreast of the latest academic papers and industry trends to integrate novel methodologies into our stack.
- Mentor a team of talented data scientists and junior researchers, fostering a collaborative and high-performance culture.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
- Minimum of 5 years of professional experience in AI/ML research or software development.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of deep learning architectures (CNNs, RNNs, Transformers, GANs).
- Strong experience with distributed computing frameworks (Apache Spark, Kubernetes) and cloud platforms (AWS, GCP).
- Exceptional problem-solving skills and the ability to work independently in a fast-paced, ambiguous environment.