Job Description
Are you ready to define the future of technology?
Nexus 2026 Labs is at the forefront of the next industrial revolution. We are building the foundational infrastructure for the 2026 tech ecosystem, focusing on Agentic AI, scalable inference, and quantum-ready algorithms. We are looking for a visionary Senior AI Engineer to join our elite engineering team and help us architect the systems that will power the next decade of intelligent applications.
In this role, you won't just maintain legacy systems; you will build the 2026 Tech Stack from the ground up. You will work directly with our research scientists and backend architects to deploy cutting-edge Large Language Models (LLMs) and generative AI agents that redefine user interaction.
Responsibilities
- Architect 2026-Ready Systems: Design and implement scalable, high-performance AI architectures capable of handling millions of concurrent inference requests.
- Model Optimization: Engineer efficient model quantization, pruning, and distillation pipelines to maximize throughput on GPU clusters.
- Agentic Workflow Development: Build autonomous agent frameworks that can reason, plan, and execute complex multi-step tasks within secure environments.
- Infrastructure Scaling: Collaborate with DevOps teams to containerize AI models using Docker and Kubernetes, ensuring 99.99% uptime.
- Evaluation Frameworks: Establish rigorous benchmarks and evaluation metrics to ensure model safety, accuracy, and bias mitigation.
Qualifications
- Advanced Technical Expertise: 5+ years of experience in Machine Learning, Deep Learning, or Artificial Intelligence with a focus on production environments.
- Proficiency in Python: Deep understanding of Python ecosystems, including PyTorch, TensorFlow, and JAX.
- Experience with LLMs: Strong background in training, fine-tuning, or deploying Large Language Models (e.g., GPT, Llama, BERT variants).
- Cloud Architecture: Hands-on experience with cloud platforms (AWS, GCP, or Azure) and serverless computing architectures.
- Software Engineering Standards: Experience with CI/CD pipelines, unit testing, and code reviews using Git.
- Problem Solving: Ability to debug complex distributed systems and optimize performance under heavy load.