Job Description
We are seeking a visionary Senior AI/ML Architect to spearhead our 2026 Technology Roadmap. As we prepare to redefine the boundaries of artificial intelligence, you will design the infrastructure for next-generation generative models and autonomous systems. This is an opportunity to work on cutting-edge technology that will define the landscape of the future.
Our Mission
At Nexus Future Systems, we are building the engines of tomorrow. Our team is dedicated to pushing the limits of what is possible with Large Language Models (LLMs), Quantum Computing integration, and Edge AI.
Key Responsibilities
- Architect and implement scalable AI systems tailored for the 2026 ecosystem.
- Lead the research and development of proprietary Generative AI models.
- Optimize deep learning inference pipelines for real-time performance.
- Collaborate with cross-functional teams to integrate AI solutions into consumer products.
- Establish best practices for MLOps, model governance, and ethical AI usage.
Qualifications
- PhD or Master’s degree in Computer Science, AI, or a related technical field.
- 7+ years of experience in machine learning, deep learning, or AI engineering.
- Expert proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Proven track record of deploying large-scale models into production environments.
- Strong understanding of distributed systems and cloud architecture (AWS/Azure/GCP).
Responsibilities
- Architect and implement scalable AI systems tailored for the 2026 ecosystem.
- Lead the research and development of proprietary Generative AI models.
- Optimize deep learning inference pipelines for real-time performance.
- Collaborate with cross-functional teams to integrate AI solutions into consumer products.
- Establish best practices for MLOps, model governance, and ethical AI usage.
Qualifications
- PhD or Master’s degree in Computer Science, AI, or a related technical field.
- 7+ years of experience in machine learning, deep learning, or AI engineering.
- Expert proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Proven track record of deploying large-scale models into production environments.
- Strong understanding of distributed systems and cloud architecture (AWS/Azure/GCP).