Job Description
Job Title:
Sr. AI/ML Engineer Location:
Austin, TX, (Hybrid)- On Site and Telework Position Type:
Contract Interview Mode:
MS Teams & In-person Key Responsibilities:
Design, develop, and maintain software services supporting engineering workflows Implement model ingestion pipelines and automate quantity extraction processes Build and enhance plan conformance validation systems Develop and maintain CI/CD pipelines to support automated integration and deployment Extend AI-based proof-of-concept solutions into scalable, production-ready applications Develop secure, responsive, and user-friendly web applications Integrate AI/ML models into enterprise systems and engineering workflows Ensure compliance with procurement and organizational standards using PEPS Collaborate with cross-functional teams including engineers, analysts, and stakeholders Optimize application performance, scalability, and reliability II. CANDIDATE SKILLS AND QUALIFICATIONS
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, 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
