Software Developer Specialist

The Smart
Austin, TX, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Airflow Amazon Web Services Computer Vision Microsoft Azure Bash Shell Big Data Program Optimization Databases Continuous Integration Information Engineering
+45 more
Data Governance Data Visualization DevOps Distributed Computing Environment Github Monitoring of Systems Python (Programming Language) PostgreSQL Machine Learning MySQL Natural Language Processing Node.Js NoSQL Object Detection OpenCV Open Source Technology Windows PowerShell Recommender Systems Ansible Tensorflow Software Engineering Spatial Data Infrastructures Web Applications Digital Twin Scripting Google Cloud Enterprise Software Applications Cloud Platform System Feature Engineering Pytorch System Availability Large Language Models Prompt Engineering Containerization AI Platforms Kubernetes Infrastructure Automation Frameworks HuggingFace Machine Learning Operations Unreal Engine Oracle Cloud Infrastructure GPT Data Pipelines Docker Jenkins

Job description

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

Requirements

Do you have experience in Time series models?, * 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.

Benefits & conditions

  • Competitive salary

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