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# Machine Learning Engineer-Mid

- **Company:** The Intersect Group
- **Location:** Irving, TX, United States
- **Experience:** Experienced
- **Contract:** Contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Software Quality, Databases, Data Cleansing, Information Engineering, Data Systems, Cursor, Distributed Systems, Python (Programming Language), Machine Learning, NoSQL, Software Engineering, Software Systems, Google Cloud, Cloud Platform System, Feature Engineering, GitHub Copilot, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Backend, Information Technology, Machine Learning Operations, Api Design, Docker, Databricks, Programming Languages, Microservices
- **Published:** November 3, 2026
- **Apply:** https://www.dice.com/job-detail/c8a5b231-0ca9-499b-8d4b-10fcd1a51d88

## About the Role

* Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related technical field (or equivalent practical experience).
 * 2+ years of experience with feature engineering, data preparation, and statistical modeling techniques.
 * 2+ years of experience training, evaluating, and deploying machine learning and AI models in production environments.
 * Hands-on experience developing solutions utilizing large language models (LLMs) and generative AI technologies.
 * Experience building advanced AI systems utilizing vector databases, embeddings, retrieval-augmented generation (RAG), memory architectures, or similar technologies.
 * Experience deploying and managing machine learning workloads within cloud environments.
 * Familiarity with MLOps practices and the operationalization of AI solutions.
 * Experience with containerization and orchestration technologies such as Docker and Kubernetes.
 * Strong software development skills and proficiency in Python or similar programming languages.

Preferred Qualifications

 * Experience with Databricks or comparable data and AI platforms.
 * Experience developing APIs, backend services, and integrated data solutions.
 * Familiarity with modern databases, both relational and NoSQL.
 * Experience building and supporting production-grade AI systems.
 * Experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, Amazon Q, or similar platforms).
 * Exposure to cloud-native architectures and scalable distributed systems.

Desired Skills

 * Generative AI and LLM application development
 * Retrieval-Augmented Generation (RAG)
 * Prompt engineering and AI orchestration frameworks
 * Vector databases and embeddings
 * Machine learning model development and deployment
 * Python development
 * Cloud platforms (Azure, AWS, or Google Cloud Platform)
 * Docker and Kubernetes
 * API and microservices development
 * MLOps and production AI systems

This position offers the opportunity to work on cutting-edge AI initiatives while helping shape enterprise-scale solutions that directly impact business outcomes and customer experiences.

## Description

As an AI Engineer II, you will design, develop, and deploy AI/ML solutions that enhance customer experiences, improve operational efficiency, and enable innovative digital products. The ideal candidate combines strong machine learning expertise with hands-on software engineering skills and a passion for staying current with advancements in artificial intelligence, large language models (LLMs), and cloud technologies., * Research, prototype, and develop AI-driven software solutions to solve complex business challenges.

 * Design, build, and deploy machine learning and generative AI applications into production environments.
 * Develop and optimize solutions leveraging large language models (LLMs), vector databases, retrieval techniques, and memory frameworks.
 * Collaborate closely with cross-functional teams including data engineering, product management, architecture, and user experience.
 * Evaluate emerging AI technologies, frameworks, and tools and recommend adoption where appropriate.
 * Ensure high standards of code quality, scalability, reliability, and performance.
 * Participate throughout the solution lifecycle, from experimentation and proof-of-concept development to production deployment and monitoring.
 * Deliver projects on schedule while maintaining a strong focus on innovation and engineering excellence.