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# AI/ML Engineer

- **Company:** PRISTINNO TECHNOLOGY LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Business Software, Data Cleansing, Data Security, Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, Systems Integration, Google Cloud, Feature Engineering, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Model Validation, Generative AI, Git, Scikit Learn, Kubernetes, Machine Learning Operations, Restful APIs, Docker, Unsupervised Learning
- **Published:** October 15, 2026
- **Apply:** https://www.dice.com/job-detail/10d5210b-7e0f-463a-824a-490444458f2f

## About the Role

We are looking for an experienced AI/ML Engineer to design, develop, and deploy machine learning solutions and AI-powered applications. The ideal candidate will have strong Python programming skills, hands-on experience with machine learning frameworks, and a solid understanding of AI model development and deployment., * 5+ years of experience in software development, data science, or machine learning.

 * Strong proficiency in Python.
 * Hands-on experience with TensorFlow, PyTorch, or Scikit-learn.
 * Good understanding of supervised and unsupervised learning algorithms.
 * Experience with data preprocessing, feature engineering, and model evaluation.
 * Familiarity with REST APIs and integrating ML models into applications.
 * Experience with Git and collaborative development practices.

Preferred Qualifications

 * Experience with Generative AI, LLMs, LangChain, or RAG.
 * Familiarity with AWS, Microsoft Azure, or Google Cloud Platform.
 * Knowledge of Docker, Kubernetes, or MLflow.
 * Experience deploying and monitoring machine learning models in production.

## Description

* Design, develop, train, and deploy machine learning models for business applications.
 * Build AI-powered solutions using Python and modern machine learning frameworks.
 * Work with structured and unstructured datasets to develop predictive models.
 * Implement and optimize machine learning algorithms for accuracy, scalability, and performance.
 * Collaborate with data engineers, software developers, and business teams to integrate AI/ML solutions.
 * Develop and maintain model pipelines for training, testing, deployment, and monitoring.
 * Explore Generative AI, large language models (LLMs), and retrieval-augmented generation (RAG) solutions.
 * Follow best practices for model evaluation, data security, and responsible AI development.