Job Description
Join the Architects of the 2026 Future.
Nebula AI Systems is pioneering the next generation of autonomous intelligence. We are looking for a visionary Senior AI Engineer to spearhead the development of our next-gen Large Language Models (LLMs) and generative AI frameworks. If you are passionate about pushing the boundaries of what's possible in artificial intelligence and want to define the roadmap for 2026 and beyond, this is your opportunity to lead at the forefront of innovation.
Why Join Us?
- Work on mission-critical projects that will redefine human-computer interaction.
- Competitive equity package and top-tier healthcare benefits.
- Flexible remote-first culture with state-of-the-art equipment.
- Direct mentorship from industry veterans in deep learning and NLP.
Role Overview:
As a Senior AI Engineer, you will be responsible for designing, training, and deploying cutting-edge machine learning systems. You will work closely with our research team to bridge the gap between theoretical breakthroughs and scalable production systems.
Responsibilities
- Design, train, and optimize state-of-the-art deep learning models, specifically focusing on Transformers and Generative AI architectures.
- Collaborate with data scientists and product managers to define AI product requirements and technical roadmaps.
- Implement rigorous testing and evaluation frameworks to ensure model accuracy, fairness, and robustness.
- Optimize inference pipelines for low-latency, high-throughput deployment on cloud infrastructure.
- Mentor junior engineers and contribute to the technical culture of the engineering team.
- Stay ahead of industry trends in AI research and integrate relevant advancements into our core technology stack.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.
- 5+ years of professional experience in machine learning, deep learning, or NLP.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Strong experience with large-scale distributed training and model fine-tuning.
- Proven track record of deploying ML models to production environments.
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.