Benefits:
Competitive salary
Location
Hybrid in Austin, TX
Experience Level
Senior (8+ years relevant experience)
Role Overview
The Software Developer Specialist will support the development and productionization of advanced AI-driven applications for transportation engineering workflows. This role focuses on transforming proof-of-concept machine learning models into scalable, secure, and user-friendly web applications. The position operates within a cloud-first environment and emphasizes MLOps, automation, and integration of AI solutions into enterprise systems.
Key Responsibilities
AI/ML Application Development
Convert prototype AI/ML models into production-ready web applications
Develop solutions supporting engineering workflows such as plan review automation, asset detection, and digital delivery
Implement NLP, computer vision, and recommendation system capabilities into real-world applications
Optimize and maintain deployed machine learning models for performance and scalability
Data Engineering & Model Operations
Build and manage data pipelines, feature engineering workflows, and feature stores
Support distributed model training and large-scale data processing
Implement model optimization techniques such as quantization, pruning, and distillation
Develop time series models for forecasting, anomaly detection, and monitoring systems
DevOps & CI/CD Automation
Design and maintain CI/CD pipelines for application and model deployment
Utilize containerization and orchestration tools (Docker, Kubernetes) for scalable deployments
Automate infrastructure and workflows using tools such as Ansible and scripting (Bash/PowerShell)
Manage model lifecycle and experiment tracking using MLOps platforms
Cloud Platform Delivery
Deploy and manage AI/ML workloads across cloud environments (AWS, Azure, GCP, OCI)
Leverage cloud-native AI services (e.g., SageMaker, Vertex AI, Azure AI)
Ensure high availability, scalability, and security of deployed solutions
Collaboration & Stakeholder Alignment
Partner with engineering, data, and business teams to define requirements and deliver solutions
Translate technical AI/ML capabilities into practical applications for end users
Support compliance with regulatory and security requirements in a public sector environment
Required Qualifications
Technical Skills
8+ years of experience with cloud platforms (AWS, Azure, GCP, or OCI) for ML workloads
8+ years of DevOps experience, including CI/CD pipelines, Docker, Kubernetes, and automation tools
8+ years working with databases (PostgreSQL, MySQL, NoSQL, and vector databases)
Advanced scripting experience with Bash and PowerShell
Strong experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins, or similar)
3+ years of production-level Python development (primary language)
AI/ML Expertise
Hands-on experience with NLP/LLMs (BERT, GPT, T5, transformers, RAG systems, prompt engineering, fine-tuning)
Experience building and deploying production ML models used by real users
Background in computer vision (e.g., PyTorch, TensorFlow, OpenCV, object detection, segmentation)
Experience with recommender systems and personalization models
Experience with time series modeling (forecasting, anomaly detection)
Familiarity with distributed training (multi-GPU/multi-node setups)
MLOps & Data Engineering
Experience with MLOps tools (MLflow, Kubeflow, Weights & Biases, Airflow, etc.)
Experience with feature stores (Feast, Tecton) or advanced feature engineering
Knowledge of model optimization techniques (quantization, pruning, distillation)
Experience working with open-source or non-frontier LLMs (Hugging Face, Ollama, etc.)
Preferred Qualifications
Experience with GIS and spatial data analysis
Background in transportation, logistics, or smart city domains
Experience applying computer vision to infrastructure or vehicular datasets
Familiarity with public sector compliance, data governance, and security standards
Experience with Unreal Engine or digital twin technologies
Experience with mapping/visualization tools such as Cesium or related APIs
Exposure to Polygonflow Dash or similar visualization platforms
Core Skills & Attributes
Strong analytical and problem-solving capabilities
Ability to work across AI/ML, software engineering, and infrastructure domains
Effective communication with technical and non-technical stakeholders
Experience delivering production-grade AI/ML systems
Detail-oriented with a focus on reliability, scalability, and security
Self-directed and able to operate in complex, evolving technical environments
Collaborative mindset with emphasis on practical, implementable solutions
Flexible work from home options available.