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# AI/ML Engineer

- **Company:** Robotics Technologies LLC
- **Location:** Austin, TX, United States
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Software, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Azure Machine Learning, SQL Databases, Unstructured Data, Data Processing, Enterprise Software Applications, Feature Engineering, Pytorch, Large Language Models, Prompt Engineering, Google Vertex AI, Deep Learning, Generative AI, Scikit Learn, Machine Learning Operations, Unsupervised Learning
- **Published:** October 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=3e55ffaa7c227856

## About the Role

* Python, SQL, and Machine Learning.
 * TensorFlow, PyTorch, and Scikit-learn.
 * Natural Language Processing (NLP).
 * Generative AI, LLMs, and Prompt Engineering.
 * Data Processing and Feature Engineering.
 * AWS SageMaker, Azure ML, or Google Vertex AI.
 * Model Deployment and MLOps.
 * Statistical Analysis and Predictive Modeling.

## Description

We are looking for an experienced AI/ML Engineer with strong expertise in machine learning, artificial intelligence, model development, and data-driven solutions. The candidate will be responsible for designing, developing, and deploying intelligent applications to solve complex business problems., * Design, develop, and implement machine learning models and AI-based solutions.

 * Collect, clean, preprocess, and analyze structured and unstructured datasets.
 * Build predictive models using supervised and unsupervised learning techniques.
 * Develop and optimize machine learning algorithms for business applications.
 * Work with NLP, deep learning, and generative AI technologies.
 * Integrate AI/ML models into existing enterprise applications.
 * Collaborate with data engineers and software developers to build scalable AI solutions.
 * Monitor model performance and implement continuous improvements.
 * Develop automated machine learning pipelines and workflows.
 * Document model architecture, development processes, and implementation results.