Software Engineer - Machine Learning - IV

Location: Richardson, TX

Salary: Depends on Experience

Description: 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.

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Contact:

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