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# AI/ML Developer

- **Company:** Raas Infotek LLC
- **Location:** Plano, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Microsoft Azure, Cluster Analysis, Software Code Optimization, Code Review, Databases, Continuous Integration, Data Cleansing, Distributed Systems, Github, Python (Programming Language), Machine Learning, NoSQL, NumPy, Object-Oriented Software Development, Tensorflow, Azure Machine Learning, Software Deployment, Software Engineering, SQL Databases, Unstructured Data, Explainable AI (XAI), Pinecone, Data Processing, Google Cloud, Enterprise Software Applications, Feature Engineering, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Deep Learning, Model Validation, Generative AI, Keras, Agentic-AI, Gitlab, Git, Pandas, Pyspark, Scikit Learn, Kubernetes, Information Technology, Deployment Automation, HuggingFace, Machine Learning Operations, FAISS, Restful APIs, Software Version Control, Docker, Unsupervised Learning, ChromaDB
- **Published:** October 28, 2026
- **Apply:** https://www.dice.com/job-detail/ec45b347-8aac-486c-ab98-7999f45ece1e

## About the Role

* Programming: Python, SQL, object-oriented programming, REST APIs.
 * Machine Learning: Supervised and unsupervised learning, regression, classification, clustering, feature engineering, model evaluation.
 * Deep Learning: TensorFlow, PyTorch, Keras, neural networks.
 * Generative AI: LLMs, RAG, prompt engineering, embeddings, vector databases.
 * AI Frameworks: LangChain, LangGraph, Hugging Face Transformers.
 * Data Processing: Pandas, NumPy, PySpark, data preprocessing and transformation.
 * Cloud Platforms: AWS, Azure, or Google Cloud Platform AI/ML services.
 * MLOps: MLflow, Docker, Kubernetes, CI/CD, model deployment, monitoring.
 * Databases: SQL, NoSQL, vector databases such as Pinecone, FAISS, or Chroma.
 * Version Control: Git, GitHub, or GitLab.

Preferred Qualifications

 * Experience developing production-grade Generative AI and Agentic AI applications.
 * Knowledge of fine-tuning, model optimization, and evaluation of LLMs.
 * Experience with automated ML pipelines and scalable distributed computing.
 * Familiarity with responsible AI, model governance, and explainable AI.
 * Experience working in Agile/Scrum environments.
 * Strong analytical, problem-solving, communication, and leadership skills.

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Experience Requirements

 * 12+ years of overall IT/software development experience.
 * Strong hands-on experience in AI/ML development and production deployments.
 * Proven experience designing and implementing enterprise-level AI solutions.
 * Ability to lead technical discussions and collaborate with cross-functional teams.

## Description

We are seeking an experienced Senior AI/ML Developer with 12+ years of experience in software development, machine learning, artificial intelligence, and deploying scalable AI-driven solutions. The ideal candidate will have strong hands-on experience in Python, machine learning frameworks, deep learning, Generative AI, Large Language Models (LLMs), and cloud-based AI services., * Design, develop, and deploy scalable AI/ML models to solve complex business problems.

 * Build machine learning pipelines for data preprocessing, feature engineering, model training, evaluation, and deployment.
 * Develop AI applications using Python, TensorFlow, PyTorch, and Scikit-learn.
 * Implement Generative AI solutions using LLMs, Retrieval-Augmented Generation (RAG), prompt engineering, and vector databases.
 * Develop AI agents and intelligent automation workflows using frameworks such as LangChain and LangGraph.
 * Work with structured and unstructured data to build predictive and analytical models.
 * Deploy and manage AI/ML solutions on AWS, Microsoft Azure, or Google Cloud Platform (Google Cloud Platform).
 * Build REST APIs and integrate AI/ML models with enterprise applications.
 * Optimize model performance, scalability, accuracy, latency, and resource utilization.
 * Implement MLOps practices for model versioning, monitoring, CI/CD, and automated deployment.
 * Collaborate with data engineers, software developers, architects, and business stakeholders.
 * Ensure data privacy, model security, responsible AI practices, and compliance with organizational standards.
 * Provide technical leadership, code reviews, documentation, and mentorship to development teams.