MLOps Engineer II; GPU Compute

Position: MLOps Engineer II (GPU Compute)
We are looking for a MLOps Engineer II w/ a focus on GPU Compute to join a team in Coppell, Texas, on a Long-term Contract assignment. In this role, you will design and refine vision-based AI solutions that support real-world image and video use cases, while partnering with cross-functional teams to move ideas from research into production. The position is ideal for someone who combines strong machine learning expertise with practical understanding of hardware constraints and model performance in live environments.

Responsibilities:
• Deploy GPUs (Graphics Processing Units) workflows in a retail environment that requires processing massive amounts of image, video, customer, and transaction data.
• Design, build, and enhance computer vision and machine learning models for use cases involving object detection, image segmentation, classification, and video-based analysis.
• Compare modeling approaches, assess trade-offs across accuracy, speed, and scalability, and recommend fit-for-purpose solutions aligned with business goals.
• Train and adapt deep learning models using frameworks such as PyTorch or Tensor Flow, applying techniques like transfer learning and optimization for efficient performance.
• Establish evaluation methods, track key performance measures, investigate error patterns, and iterate on models to improve reliability and response time.
• Incorporate practical considerations related to cameras, sensors, lighting conditions, and edge hardware when developing and tuning solutions.
• Create and support data preparation, annotation, and validation workflows that enable consistent experimentation and dependable deployment.
• Work closely with software, hardware, and MLOps partners to transition models from proof of concept into production-ready applications.
• Contribute to deployment readiness by helping optimize models for inference and operational use in resource-constrained environments.