AI/ML Developer

Job ID: TX-RITM1788244

Hybrid/Local AI/ML Developer/Cloud Engineer (AWS/Azure/Google Cloud Platform/OCI/15+) with DevOps, SageMaker/Bedrock/Vertex AI, Ansible/CI/CD/Docker/Kubernetes, PostgreSQL/MySQL/NoSQL/vector db, Bash/PowerShell, GitHub Actions/Jenkins, Python, NLP/LLMs/BERT/GPT/T5/RAG, MLflow/Kubeflow/Airflow, Distributed Training, Computer Vision, PyTorch/TensorFlow/OpenCV/YOLO, Feast/Tecton, Ollama/Huggingface, GIS, Cesium API, Polygonflow experience

Location: Austin, TX (DOT)
Duration: 12 Months

Skills:
8 Required Cloud Platforms: Experience with AWS, Azure, Google Cloud Platform, or OCI for deploying and managing ML workloads. We leverage AI/ML tools across all major cloud providers (Azure AI, AWS SageMaker/Bedrock, Google Cloud Platform Vertex AI, OCI AI Services).
8 Required DevOps: Ansible, CI/CD, Docker and Kubernetes experience.
8 Required Databases: SQL (PostgreSQL, MySQL) and NoSQL/vector databases.
8 Required Scripting: Proficient in both Bash and PowerShell for automation.
8 Required CI/CD Experience: Azure DevOps, GitHub Actions, Jenkins, or similar automation pipelines.
3 Required Python: 3-5+ years production experience, this is your primary language.
3 Required NLP/LLMs: Experience with transformers (BERT, GPT, T5), RAG systems, fine-tuning, prompt engineering, or building LLM applications.
3 Required Time Series: Forecasting models, anomaly detection, sequential data modeling, or real-time monitoring systems.
3 Required Recommender Systems: Collaborative filtering, ranking models, personalization engines, or content recommendations.
3 Required MLOps Tools: Production experience with MLflow, Weights & Biases, Kubeflow, Airflow, or similar platforms.
3 Required Distributed Training: Large-scale model training, multi-GPU/multi-node setups, efficient data parallelism.
3 Required Computer Vision: Production CV experience with PyTorch/TensorFlow, OpenCV, YOLO, object detection, segmentation, or real-time inference.
3 Required Feature stores (Feast, Tecton) or advanced feature engineering.
3 Required Model optimization: quantization, pruning, knowledge distillation.
3 Required LLM Models: Ollama, Huggingface, or other non-frontier models
2 Required AI/ML Production: Built and deployed 2-3+ ML models serving real users, not just experiments.
1 Preferred Experience with Geospatial Information Systems (GIS) and analyzing spatial data.
1 Preferred Prior experience in the transportation, logistics, or smart city sectors.
1 Preferred Background in Computer Vision (object detection, image segmentation) applied to infrastructure or vehicular data.
1 Preferred Familiarity with public sector data compliance, security, and governance standards.
1 Preferred Experience with the Unreal gaming engine and real world digital twinning
1 Preferred Experience with Google Maps Cesium API
1 Preferred Experience with Polygonflow Dash and its capabilities

Description:
A Software Developer Specialist will focus on engineering-related software services, including model ingestion, automated quantity extraction, plan conformance checks, and CI/CD automation. Leveraging PEPS ensures compliance with procurement regulations while enabling rapid onboarding of specialized talent.

The Senior Software Developer Specialist will be responsible for advancing TxDOT s AI initiatives by extending existing proof-of-concept (POC) solutions into scalable, production-ready web applications that directly support transportation engineering workflows. This role will focus on transforming early-stage AI models and prototypes such as those supporting plan review automation, roadway asset detection, and digital delivery into fully integrated applications accessible through secure, user-friendly web interfaces across the enterprise.

Term of Service: The initial term of the contract shall commence upon execution of the contract and expires one year from commencement with the option to renew for two, one-year period(s) at TxDOT s sole discretion. TxDOT will provide an intent to renew, in writing, a minimum of 30 days prior to expiration of the current term.