Job Description
Join the vanguard of the next technological revolution. Nebula Systems is seeking a visionary Senior AI/ML Architect to lead the development of cutting-edge Artificial General Intelligence (AGI) frameworks. In this pivotal role, you will architect the neural architectures that will define the landscape of 2026 and beyond, bridging the gap between theoretical deep learning and real-world application.
Our mission is to democratize intelligence. As a Senior Architect, you will not just write code; you will build the cognitive foundation for the next generation of autonomous agents and predictive analytics engines. If you are passionate about pushing the boundaries of what is possible in machine learning and want to leave a lasting legacy in the tech industry, we want to hear from you.
Responsibilities
- Architect Next-Gen Models: Design and implement scalable, high-performance neural network architectures for Large Language Models (LLMs) and reinforcement learning systems.
- R&D Leadership: Lead research initiatives to explore emerging paradigms in unsupervised learning, generative adversarial networks (GANs), and multi-modal AI.
- System Optimization: Oversee the full machine learning lifecycle, from data ingestion and preprocessing to model deployment and real-time inference optimization.
- Team Mentorship: Guide junior engineers and data scientists, fostering a culture of innovation, code excellence, and continuous learning within the research division.
- Strategic Planning: Collaborate with product leadership to define technical roadmaps and ensure our AI capabilities align with future market demands.
- Ethical AI Governance: Implement frameworks to ensure AI transparency, fairness, and safety in all deployed systems.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Mathematics, or a related quantitative field.
- Technical Expertise: Extensive experience (7+ years) in designing and deploying production-grade machine learning systems.
- Core Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep Learning: Strong understanding of transformer architectures, attention mechanisms, and state-of-the-art NLP techniques.
- Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems with innovative technical solutions.