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# AI/ML Developer

- **Company:** Quantum Technologies
- **Location:** Richmond, VA, United States
- **Salary:** $166,400.0
- **Contract:** Contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Microsoft Azure, Software Code Optimization, Computer Programming, Data Cleansing, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Unstructured Data, Google Cloud, Feature Engineering, Pytorch, Deep Learning, Generative AI, Pandas, Scikit Learn, Kubernetes, Machine Learning Operations, Restful APIs, Docker, Microservices
- **Published:** October 31, 2026
- **Apply:** https://www.dice.com/job-detail/0aca0d90-8d52-4bf8-8290-948a8661257a

## About the Role

* Strong programming experience in Python.
 * Hands-on experience with Machine Learning algorithms.
 * Knowledge of Deep Learning and Neural Networks.
 * Experience with TensorFlow, PyTorch, or Scikit-learn.
 * Strong knowledge of NumPy, Pandas, and data preprocessing.
 * Experience with NLP and Generative AI is preferred.
 * Knowledge of REST APIs and Microservices.
 * Experience with AWS, Azure, or Google Cloud Platform.
 * Understanding of Docker, Kubernetes, and MLOps.
 * Strong analytical and problem-solving skills.

## Description

We are seeking an experienced AI/ML Developer to design, develop, train, and deploy machine learning and artificial intelligence solutions. The ideal candidate should have strong Python programming skills, machine learning expertise, deep learning knowledge, and experience building scalable AI applications., * Design, develop, and implement AI/ML models and algorithms.

 * Build, train, test, and deploy machine learning models.
 * Develop predictive models using structured and unstructured data.
 * Work with deep learning frameworks and neural networks.
 * Perform data preprocessing, feature engineering, and model optimization.
 * Develop and integrate AI solutions using APIs and microservices.
 * Implement model monitoring, evaluation, and performance improvements.
 * Collaborate with data scientists, engineers, and business teams.
 * Deploy AI/ML models on cloud platforms.
 * Maintain technical documentation and follow MLOps best practices.