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# AI Developer

- **Company:** Aquent
- **Location:** Southlake, TX, United States
- **Experience:** Expert
- **Salary:** $155,000.0 - $195,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Cloud Computing, Code Review, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, Natural Language Processing, Recommender Systems, SQL Databases, Large Language Models, Prompt Engineering, Deep Learning, Kubernetes, Machine Learning Operations, Api Design, Data Pipelines, Docker, Microservices
- **Published:** October 5, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=3005093302-2

## About the Role

* Python
 * Machine learning engineering
 * Deep learning frameworks (Tensor
 * Flow/Py
 * Torch)
 * Natural language processing (NLP)
 * Large Language Models (LLMs) and prompt engineering
 * MLOps and model deployment (Docker, Kubernetes, CI/CD)
 * Cloud platforms (AWS, GCP, or Azure)
 * Data engineering (ETL, data pipelines)
 * SQL and No
 * SQL databases
 * API design and microservices

## Description

Aquent Talent seeks a Senior AI Developer to design and deploy cutting-edge AI solutions that power talent matching and digital experiences for global clients. You'll build scalable ML models, LLM- and NLP-driven features, and data pipelines that improve how companies find and engage creative and marketing talent. Partnering with cross-functional teams, you'll own projects from experimentation through production, mentor engineers, and establish best practices. Join a people-first, inclusive, flexible environment where you can shape the future of work and continuously grow your technical and leadership skills., * Design, build, and deploy advanced AI and machine learning solutions for Aquent Talent and its clients

 * Develop scalable models and APIs that power talent matching, personalization, and workflow automation
 * Partner with product, data, and engineering teams to translate business needs into AI-driven features
 * Evaluate and implement state-of-the-art models (LLMs, NLP, recommendation systems, predictive analytics)
 * Optimize models for performance, cost, and reliability in production environments
 * Establish best practices for data pipelines, experimentation, and model lifecycle management
 * Mentor junior engineers and contribute to architecture, code reviews, and technical standards
 * Monitor AI systems in production, analyze results, and iterate based on performance and user feedback