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Job Description
Key Responsibilities 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. Required Skills & Experience 8+ years of experience with cloud platforms including AWS, Azure, Google Cloud Platform, 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