AI/ML & Cloud Engineering

This role focuses on AI-driven automation, computer vision, digital delivery, roadway asset detection, plan review automation, CI/CD engineering, and cloud-native ML deployment across enterprise environments., * Design, develop, and deploy scalable AI/ML-powered web applications.

• Extend existing proof-of-concept AI models into enterprise production solutions.
• Build secure and user-friendly interfaces for engineering and transportation workflows.
• Develop automated quantity extraction and plan conformance systems.
• Implement CI/CD pipelines and cloud-native deployment strategies.
• Integrate NLP, computer vision, and time-series AI models into operational environments.
• Support MLOps, distributed model training, and real-time inference systems.
• Collaborate with cross-functional engineering and infrastructure teams.

• 8+ years of experience with cloud platforms including AWS, Azure, GCP, or OCI.
• 8+ years of DevOps experience using Docker, Kubernetes, Ansible, and CI/CD pipelines.
• Strong database expertise with PostgreSQL, MySQL, NoSQL, and vector databases.
• Advanced scripting experience using Bash and PowerShell.
• Hands-on experience with Azure DevOps, Jenkins, GitHub Actions, or similar tools.
• 3+ years of production Python development experience.
• Experience with NLP/LLMs including GPT, BERT, T5, RAG systems, prompt engineering, and fine-tuning.
• Experience developing and deploying AI/ML models serving real users.
• Expertise in Computer Vision using PyTorch, TensorFlow, OpenCV, YOLO, object detection, and segmentation.
• Experience with MLOps tools such as MLflow, Kubeflow, Airflow, or Weights & Biases.
• Knowledge of distributed training, feature engineering, model optimization, and vector-based AI systems.
• Experience with Hugging Face, Ollama, or other non-frontier LLM platforms.