Job Description
Shape the Future of Intelligence.
Nexus Future Systems is pioneering the architectural blueprints for the 2026 technological landscape. We are seeking a visionary AI Research Engineer to lead the development of next-generation Generative AI models and scalable Machine Learning infrastructures.
In this pivotal role, you will bridge the gap between theoretical AI research and real-world application, ensuring our solutions are robust, ethical, and ready for the challenges of the coming decade. Join a team of world-class engineers and data scientists committed to pushing the boundaries of what is possible.
Why Join Us?
- Work on cutting-edge projects that define the 2026 tech standard.
- Competitive equity and benefits package.
- Flexible remote-first culture with premium San Francisco amenities.
- Access to the latest hardware for AI training.
Responsibilities
- Design and implement proprietary Large Language Models (LLMs) and multimodal architectures optimized for 2026 standards.
- Optimize model inference pipelines for high-throughput, low-latency environments using edge computing and distributed systems.
- Conduct rigorous research on novel deep learning techniques, including Reinforcement Learning and Neuromorphic Computing.
- Collaborate with product teams to translate research findings into scalable software solutions.
- Ensure AI ethical guidelines and bias mitigation strategies are integrated into all development cycles.
- Mentor junior engineers and contribute to the technical vision of the department.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence.
- Minimum of 5 years of professional experience in Machine Learning Engineering, Deep Learning, or AI Research.
- Extensive experience with Python, PyTorch, TensorFlow, and CUDA.
- Proven track record of publishing research in top-tier conferences (NeurIPS, ICML, ACL) or open-source contributions.
- Strong understanding of distributed training, MLOps, and cloud infrastructure (AWS, GCP, Azure).
- Experience with prompt engineering and fine-tuning large language models.