Software Developer Specialist (AIML)
Job Location:
Austin, TX - USA
Monthly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
Key Skills Required:
- Python (Production Experience)
- AI/ML Model Development & Deployment
- NLP LLMs RAG Prompt Engineering
- Computer Vision (YOLO OpenCV PyTorch TensorFlow)
- MLOps (MLflow Kubeflow Airflow W&B)
- Cloud Platforms (AWS Azure GCP OCI)
- Docker Kubernetes Ansible
- CI/CD (Azure DevOps GitHub Actions Jenkins)
- SQL & NoSQL Databases
- Bash & PowerShell Scripting
- Distributed Training & Model Optimization
Preferred:
- GIS / Spatial Data
- Transportation or Smart City Experience
- Digital Twin Technologies
- Unreal Engine
- Google Maps Cesium API
- Polygonflow Dash
Minimum Requirements: Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will be displayed to customers but may not be chosen for this opportunity. | ||
| Years | Required/Preferred | Experience |
| 8 | Required | Cloud Platforms: Experience with AWS Azure GCP or OCI for deploying and managing ML workloads. We leverage AI/ML tools across all major cloud providers (Azure AI AWS SageMaker/Bedrock GCP 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 |
Required Skills:
Software Developer Specialist (AI/ML) Location: Austin TX (Hybrid) Duration: 12 Months (2 Possible 1-Year Extensions Job Description: seeking a senior Software Developer Specialist with strong Artificial Intelligence and Machine Learning expertise to transform existing AI proof-of-concepts into scalable production-ready applications supporting transportation engineering workflows roadway asset detection plan review automation and digital delivery initiatives. Required Skills: 3 years of hands-on Python development in production environments Experience building and deploying AI/ML solutions serving real users Strong experience with LLMs NLP RAG architectures Prompt Engineering and Generative AI applications Experience with Hugging Face Ollama GPT BERT T5 Transformers and other open-source AI models Computer Vision expertise using OpenCV YOLO PyTorch and TensorFlow Experience with distributed model training model optimization quantization pruning and knowledge distillation Experience developing recommender systems forecasting models anomaly detection and time-series analytics MLOps experience with MLflow Kubeflow Airflow Weights & Biases (W&B) or similar platforms Experience with Feature Stores such as Feast or Tecton Cloud expertise in AWS Azure GCP or OCI AI platforms Strong experience with Docker Kubernetes Ansible and Infrastructure Automation CI/CD experience using Azure DevOps GitHub Actions Jenkins or equivalent Experience with SQL databases (PostgreSQL MySQL) and NoSQL/Vector Databases Strong Bash and PowerShell scripting skills Preferred Skills: GIS and Geospatial Data Analytics Transportation Logistics or Smart City domain experience Digital Twin technologies Unreal Engine Google Maps Cesium API Polygonflow Dash Public Sector or State Government experience Key Responsibilities: Design develop and deploy scalable AI/ML applications Build and optimize LLM-powered solutions and RAG systems Develop Computer Vision solutions for roadway and infrastructure analysis Implement MLOps pipelines and automated model deployment processes Optimize model performance and scalability for production environments Collaborate with business engineering and transportation stakeholders Support cloud-native AI solutions across AWS Azure GCP and OCI Keywords: Python AI Machine Learning Deep Learning Generative AI LLM NLP RAG Prompt Engineering Hugging Face Ollama PyTorch TensorFlow OpenCV YOLO Computer Vision MLflow Kubeflow Airflow MLOps Docker Kubernetes Azure DevOps Jenkins GitHub Actions AWS Azure GCP OCI PostgreSQL NoSQL Vector Databases Distributed Training Feature Engineering Feature Store GIS Digital Twin.
