Job Description
Are you ready to shape the intelligence of tomorrow? Nexus Future Systems is seeking a visionary Senior AI Research Engineer to architect the next generation of generative models. As we map our trajectory toward the 2026 AI standard, we need a technical leader who isn't just building models, but defining the future of synthetic intelligence.
In this role, you will lead high-impact research initiatives, optimize deep learning architectures for massive scale, and collaborate with cross-functional teams to deploy cutting-edge AI solutions. If you are passionate about the intersection of neuroscience and software engineering, and want to leave a legacy in the AI landscape of 2026, we want to meet you.
Why Join Us?
- Work on the bleeding edge of AI research.
- Competitive compensation and equity packages.
- Flexible remote-first policy with a premium office in SF.
- Access to the latest hardware for AI training.
Join us in building the future of technology.
Responsibilities
- Design and implement state-of-the-art (SOTA) deep learning models, specifically focusing on LLMs and Transformer architectures.
- Conduct rigorous research to improve model accuracy, efficiency, and scalability for production environments.
- Lead the end-to-end machine learning lifecycle, from data preprocessing and feature engineering to model deployment and monitoring.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Collaborate with product teams to translate complex AI capabilities into user-centric applications.
- Stay abreast of the latest academic papers and industry trends to ensure our technology remains ahead of the curve.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Minimum of 5+ years of experience in research or software engineering roles within the AI industry.
- Deep expertise in Python, PyTorch, or TensorFlow.
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR) or shipping significant AI products.
- Strong understanding of MLOps, cloud infrastructure (AWS/GCP), and distributed systems.
- Excellent problem-solving skills and the ability to work in a fast-paced, dynamic startup environment.