AI/ML Software Developer Specialist

Carlin Shayn
Austin, United States of America
3 days ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Austin, United States of America

Tech stack

Clean Code Principles
Web Interfaces
Geographic Information Systems
API
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Data analysis
Computer Vision
Automated Storage and Retrieval Systems
Azure
Bash
Cloud Computing
Program Optimization
Encodings
Databases
Image Analysis
Continuous Integration
DevOps
Distributed Computing Environment
Github
Google Maps
Monitoring of Systems
Python
PostgreSQL
Machine Learning
MySQL
NoSQL
Object Detection
OpenCV
Open Source Technology
Powershell
Recommender Systems
Ansible
TensorFlow
Web Application Security
Software Engineering
SQL Databases
Digital Twin
Data Logging
Data Processing
Scripting (Bash/Python/Go/Ruby)
Google Cloud Platform
Application Enhancement Tool
Feature Engineering
PyTorch
Large Language Models
Prompt Engineering
Model Validation
Generative AI
Build Management
AI Platforms
Kubernetes
Infrastructure Automation Frameworks
HuggingFace
Data Analytics
Data Management
Machine Learning Operations
Unreal Engine
Oracle Cloud Infrastructure
GPT
Software Version Control
Docker
Jenkins

Job description

We are seeking an experienced AI/ML Software Developer Specialist to support and expand enterprise Artificial Intelligence initiatives. This role will be responsible for transforming existing proof-of-concept (POC) AI solutions into scalable, secure, and production-ready applications that support transportation engineering, infrastructure management, roadway asset detection, plan review automation, and digital delivery programs.

The selected candidate will work closely with engineering, data science, cloud, and DevOps teams to design, develop, deploy, and maintain advanced AI-powered applications accessible through enterprise web interfaces. The ideal candidate will possess a strong software engineering background combined with hands-on expertise in Machine Learning, Large Language Models (LLMs), Computer Vision, MLOps, cloud platforms, and modern DevOps practices., < data-start="1237" data-end="1271">AI/ML Application Development

  • Design, develop, and deploy production-grade AI/ML applications supporting engineering and infrastructure workflows.
  • Convert experimental AI prototypes into scalable enterprise solutions.
  • Develop secure web-based interfaces for AI-powered tools and services.
  • Build APIs and backend services to support machine learning applications and integrations.

< data-start="1631" data-end="1670">Large Language Models (LLMs) & NLP

  • Develop and deploy Retrieval-Augmented Generation (RAG) systems.
  • Fine-tune and optimize transformer-based models including BERT, GPT, T5, and related architectures.
  • Implement prompt engineering strategies and model evaluation frameworks.
  • Deploy and manage open-source and non-frontier LLMs using platforms such as Hugging Face and Ollama.

< data-start="2019" data-end="2049">Computer Vision Solutions

  • Build and deploy computer vision applications for asset detection, infrastructure monitoring, and image analysis.
  • Develop object detection, image segmentation, and real-time inference systems.
  • Utilize frameworks such as PyTorch, TensorFlow, OpenCV, and YOLO.

< data-start="2316" data-end="2355">MLOps & Model Lifecycle Management

  • Design and maintain ML pipelines for training, testing, deployment, monitoring, and retraining.
  • Implement model tracking, experiment management, and version control.
  • Utilize MLOps tools including MLflow, Kubeflow, Airflow, Weights & Biases, and similar platforms.
  • Optimize model performance through quantization, pruning, and knowledge distillation.

< data-start="2715" data-end="2754">Cloud & Infrastructure Engineering

  • Deploy and manage AI/ML workloads across major cloud platforms including AWS, Azure, Google Cloud Platform, and OCI.
  • Develop scalable infrastructure using containers and orchestration platforms.
  • Support distributed training environments and large-scale model deployment.

< data-start="3015" data-end="3039">DevOps & Automation

  • Build and maintain CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or similar tools.
  • Automate infrastructure provisioning and deployment processes using Ansible and scripting tools.
  • Implement monitoring, logging, and operational support processes.

< data-start="3308" data-end="3341">Data Engineering & Analytics

  • Work with structured and unstructured datasets.
  • Design and optimize SQL and NoSQL databases.
  • Implement vector databases and embedding-based retrieval systems.
  • Develop advanced feature engineering workflows and feature store integrations.

< data-start="3589" data-end="3620">Collaboration & Governance

  • Collaborate with business stakeholders, engineers, data scientists, and technical teams.
  • Ensure compliance with organizational security, governance, and data management standards.
  • Document technical architectures, deployment procedures, and operational processes.

Requirements

Cloud Platforms - 8+ Years

  • Experience deploying and managing AI/ML workloads on AWS, Azure, Google Cloud Platform, or OCI.
  • Experience with services such as Azure AI, AWS SageMaker/Bedrock, Google Cloud Platform Vertex AI, or OCI AI Services.

DevOps & Infrastructure - 8+ Years

  • Docker
  • Kubernetes
  • Ansible
  • CI/CD automation

Databases - 8+ Years

  • PostgreSQL
  • MySQL
  • NoSQL databases
  • Vector databases

Scripting & Automation - 8+ Years

  • Advanced proficiency in Bash and PowerShell.

CI/CD Tools - 8+ Years

  • Azure DevOps
  • GitHub Actions
  • Jenkins
  • Similar pipeline technologies

Python Development - 3+ Years

  • Production-level Python development experience.
  • Strong software engineering and coding practices.

NLP & Large Language Models - 3+ Years

  • Transformer architectures
  • GPT, BERT, T5
  • Prompt engineering
  • Fine-tuning
  • RAG implementations

Time Series Analytics - 3+ Years

  • Forecasting models
  • Anomaly detection systems
  • Sequential data processing
  • Real-time monitoring

Recommender Systems - 3+ Years

  • Collaborative filtering
  • Ranking systems
  • Personalization engines
  • Recommendation algorithms

MLOps Platforms - 3+ Years

  • MLflow
  • Kubeflow
  • Airflow
  • Weights & Biases

Distributed Training - 3+ Years

  • Multi-GPU training
  • Multi-node environments
  • Data parallelism
  • Large-scale model training

Computer Vision - 3+ Years

  • PyTorch
  • TensorFlow
  • OpenCV
  • YOLO
  • Object detection and segmentation

Feature Engineering - 3+ Years

  • Feature stores such as Feast or Tecton.
  • Advanced feature engineering techniques.

Model Optimization - 3+ Years

  • Quantization
  • Pruning
  • Knowledge distillation

Open-Source LLM Platforms - 3+ Years

  • Ollama
  • Hugging Face
  • Other open-source AI ecosystems

Production AI/ML Systems - 2+ Years

  • Experience building and deploying AI/ML solutions used by real-world users in production environments., * Experience with Geographic Information Systems (GIS) and spatial analytics.
  • Transportation, logistics, infrastructure, or smart-city industry experience.
  • Computer Vision applications involving roadway, vehicular, or infrastructure datasets.
  • Knowledge of public-sector compliance, governance, and security frameworks.
  • Experience with Unreal Engine and digital twin technologies.
  • Familiarity with Google Maps and Cesium APIs.
  • Experience with Polygonflow Dash and related visualization platforms.

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