Job Description
We are not just building software for today; we are architecting the intelligence infrastructure of tomorrow. At Nebula Dynamics, we are seeking a visionary Senior AI/ML Architect to lead our next-generation research initiatives, specifically tailored for the evolving landscape of 2026. In this pivotal role, you will bridge the gap between cutting-edge theoretical AI research and scalable, production-ready systems that drive our global product lines.
If you are passionate about pushing the boundaries of what's possible in artificial general intelligence and want to define the standards for the industry, we want to hear from you.
Responsibilities
- Architectural Leadership: Define the high-level technical vision and strategy for our proprietary Machine Learning infrastructure, ensuring scalability, security, and performance.
- Model Development: Design and implement state-of-the-art deep learning models, focusing on Large Language Models (LLMs), reinforcement learning, and computer vision applications.
- System Optimization: Lead initiatives to reduce model inference latency and optimize resource utilization, ensuring real-time processing capabilities.
- MLOps Implementation: Establish and maintain robust CI/CD pipelines and MLOps frameworks (e.g., Kubernetes, Kubeflow) to automate model training, testing, and deployment.
- Collaboration: Partner with product managers, engineers, and data scientists to translate complex business requirements into elegant technical solutions.
- Talent Mentorship: Mentor junior architects and data scientists, fostering a culture of continuous learning and technical excellence within the team.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, Statistics, or a related field.
- Experience: 8+ years of professional experience in designing and deploying large-scale machine learning systems.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, and modern MLOps tooling.
- Frameworks: Strong understanding of Deep Reinforcement Learning, Natural Language Processing (NLP), and generative AI architectures.
- Cloud Mastery: Extensive experience with cloud platforms (AWS, GCP, or Azure) and distributed computing systems.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems with innovative, data-driven solutions.