Software Engineer - Machine Learning - IV

Our client is currently seeking a Software Engineer - Machine Learning - IV


This job will have the following responsibilities:

• We are seeking a highly skilled AI Systems Contractor to join our advanced AI engineering team. This role is ideal for someone with deep technical expertise in Large Language Models (LLMs) , agentic AI workflows , and high-performance computing environments . You will play a critical role in designing, building, and optimizing AI solutions that leverage NVIDIA GPUs within a Red Hat OpenShift platform.
  
  
  You'll work across the full AI development lifecycle-from rapid prototyping in Jupyter Notebooks to deploying scalable, production-grade systems.
  
  
  Responsibilities
  • Develop & Fine-Tune AI Models : Build and optimize LLMs and other deep learning models tailored to project needs.
  • Design Agentic AI Systems : Architect and implement multi-agent AI workflows capable of autonomous task execution.
  • GPU Optimization on OpenShift : Deploy and manage AI/ML workloads on OpenShift, ensuring efficient GPU utilization.
  • Python & Jupyter Development : Use Python and Jupyter for prototyping, experimentation, and model training.
  • Pipeline & Infrastructure Management : Maintain robust data/model pipelines and troubleshoot performance bottlenecks in containerized environments.
  • Cross-Functional Collaboration : Partner with data scientists, engineers, and project managers to deliver high-impact AI solutions.
  Minimum Qualifications
  • Proven experience developing AI systems, including LLMs and agentic AI architectures.
  • Advanced proficiency in Python and experience with frameworks like PyTorch , TensorFlow , LangChain , and Hugging Face .
  • Hands-on expertise with Jupyter Notebooks for model development.
  • Direct experience deploying containerized AI workloads using NVIDIA GPUs on Red Hat OpenShift .
  • Strong understanding of Docker , Kubernetes , and CI/CD practices.
  • Excellent problem-solving skills in high-performance computing environments.
  • Bachelor's degree in Computer Science, Engineering, or a related field-or equivalent practical experience.
  Preferred Qualifications
  • Experience with distributed training and model serving at scale.
  • Familiarity with MLOps tools and practices.
  • Contributions to open-source AI projects or research publications.