Job Description
Join the Architects of Tomorrow
Nebula Future Tech is pioneering the '2026 Roadmap,' a revolutionary initiative to deploy autonomous AI agents and next-generation generative models. We are seeking a visionary Senior AI Architect to design the foundational infrastructure that will define the future of human-machine interaction.
In this role, you won't just manage existing tech stacks; you will build the ecosystems that power autonomous decision-making, real-time multimodal processing, and ethical AI governance systems. If you are passionate about pushing the boundaries of what is possible in Artificial Intelligence, we want to hear from you.
Why Join Us?
- Work on cutting-edge 'Year 2026' projects that set industry standards.
- Competitive compensation and equity packages.
- Top-tier engineering team and access to the latest compute resources.
Responsibilities
- Architect and design scalable, fault-tolerant AI infrastructures capable of supporting high-frequency, real-time inference at global scale.
- Lead the research and implementation of next-generation Large Language Models (LLMs) and Agentic AI workflows.
- Optimize model performance (latency and throughput) using advanced quantization and pruning techniques.
- Define and enforce architectural standards for data pipelines, model training, and deployment (MLOps).
- Collaborate with cross-functional teams to integrate AI solutions into consumer-facing products seamlessly.
- Ensure ethical AI practices, data privacy compliance, and robust security protocols within all AI systems.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 8+ years of professional experience in Machine Learning Engineering, Deep Learning, or AI Architecture.
- Extensive proficiency in Python, PyTorch, TensorFlow, and modern MLOps tools (MLflow, Kubeflow, Airflow).
- Deep understanding of LLM architectures, RAG (Retrieval-Augmented Generation), and Vector Databases (Pinecone, Milvus).
- Proven track record of deploying production-grade AI models serving millions of requests.
- Strong background in distributed systems and cloud architecture (AWS, GCP, or Azure).