Entry Level Docker Kubernetes Jobs in Texas (NOW HIRING)

AI/ML Engineer

Location: Dallas, TX, United States
Job Type: Full-Time
Experience: 0–3 years
Work Authorization: OPT, H-1B, , or other valid US work authorization

Job Summary

We are seeking a motivated AI/ML Engineer to design, develop, train, and deploy machine learning and artificial intelligence solutions. The ideal candidate should have strong programming skills in Python and hands-on experience with machine learning, deep learning, data processing, and modern AI technologies.

Responsibilities

• Develop and implement machine learning and deep learning models.
• Perform data preprocessing, feature engineering, model training, and evaluation.
• Build AI/ML solutions using Python and popular ML frameworks.
• Work with structured and unstructured datasets.
• Develop and optimize ML pipelines for model training and deployment.
• Implement predictive models and recommendation/classification systems.
• Work with Generative AI, LLMs, prompt engineering, or RAG-based applications.
• Deploy and monitor ML models in cloud or production environments.
• Collaborate with software engineers and data teams to integrate AI/ML models into applications.
• Write clean, maintainable, and well-tested Python code.
• Analyze model performance and improve accuracy, scalability, and efficiency.

Required Skills

• Python
• Machine Learning
• Deep Learning
• TensorFlow / PyTorch
• Scikit-learn
• NumPy
• Pandas
• SQL
• Data Structures & Algorithms
• Data Preprocessing & Feature Engineering
• Model Training & Evaluation
• REST APIs
• Git

Preferred Skills

• Generative AI / LLMs
• Prompt Engineering
• RAG
• LangChain / LangGraph
• NLP or Computer Vision
• AWS / Azure / Google Cloud Platform
• Docker
• Kubernetes
• MLflow
• CI/CD
• MLOps
• PySpark

Education

• Master''s degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, Data Science, Engineering, Mathematics, or a related technical field.
• Master''s degree preferred.

Ideal Candidate

The ideal candidate has a strong academic background in AI/ML, Computer Science, Data Science, or IT and can demonstrate hands-on experience through internships, academic projects, research, GitHub repositories, or professional experience.

entry level candidates are welcome, provided they have practical AI/ML projects and strong technical fundamentals.