> Markdown version of [/jobs/ext/2028723-principal-machine-learning-engineer-mle](https://www.wearedevelopers.com/jobs/ext/2028723-principal-machine-learning-engineer-mle). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Principal Machine Learning Engineer (MLE)

- **Company:** Equinix
- **Location:** Dallas, TX, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Google App Engines, Microsoft Azure, Continuous Integration, Data Transformation, Software Design Patterns, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Software Engineering, Google Cloud, Cloud Platform System, Feature Engineering, Chatbots, Data Ingestion, Pytorch, Large Language Models, Multi-Cloud, Generative AI, Build Management, Containerization, Kubernetes, Machine Learning Operations, Software Version Control, Docker
- **Published:** August 11, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/principal-machine-learning-engineer-mle-dallas-tx-usa-58897186

## About the Role

for performance, scalability, reliability, and cost in cloud environments * Implement and maintain MLOps best practices (CI/CD, model versioning, experiment tracking, retraining) * Work with PyTorch and TensorFlow for model development * Containerize ML services and deploy via Docker, Kubernetes, App Engine, or VMs * Apply NLP fundamentals (transformers, attention, embeddings, preprocessing) * Deploy and manage models in production, conduct A/B testing, measure performance with statistics * Develop features, run experiments, translate insights into improvements * Build and deploy classical ML models and NLP/vision applications (sentiment, summarization, Q&A, chatbots, CV tasks) Tasks * PhD with 5+ years, Master with 6+ years, or Bachelor with 7+ years in ML/CS/Data Science or related field * Strong Python proficiency for ML and production systems * Solid software engineering fundamentals, system design, and design patterns * Hands-on experience with at least one major cloud platform (GCP,
Azure, AWS) * Experience building and deploying production-grade ML systems * Strong communication skills to explain technical concepts to diverse stakeholders * Excellent time management, collaboration, and organizational skills Key requirements * Employee Assistance Program * Health, life, disability insurance * Retirement plans * Paid Time Off (PTO) and holidays * Equity may be offered * Paid vacations and holidays

## Description

Experteer Overview As a Principal Machine Learning Engineer, you design, build, and scale ML and generative AI systems powering real-world products. You collaborate with AI and business teams to translate advanced ML/LLM capabilities into production-grade solutions across GCP, AWS, and Azure. The role blends ML, software engineering, and MLOps to deliver robust, scalable cloud-native systems. You will work on end-to-end pipelines and multi-cloud deployments that drive measurable impact, shaping how AI enables business outcomes. Compensation / Benefits * Design, develop, and deploy ML and LLM-based solutions for production use cases * Collaborate with Generative AI Center of Excellence leaders and stakeholders to evaluate buy vs. build for generative AI * Develop end-to-end ML pipelines (data ingestion, feature engineering, training, evaluation, deployment, monitoring) * Architect and implement LLM-powered systems across multiple clouds into a unified solution * Optimize ML workflows for performance, scalability, reliability, and cost in cloud environments * Implement and maintain MLOps best practices (CI/CD, model versioning, experiment tracking, retraining) * Work with PyTorch and TensorFlow for model development * Containerize ML services and deploy via Docker, Kubernetes, App Engine, or VMs * Apply NLP fundamentals (transformers, attention, embeddings, preprocessing) * Deploy and manage models in production, conduct A/B testing, measure performance with statistics * Develop features, run experiments, translate insights into improvements * Build and deploy classical ML models and NLP/vision applications (sentiment, summarization, Q&A, chatbots, CV tasks) Tasks * PhD with 5+ years, Master with 6+ years, or Bachelor with 7+ years in ML/CS/Data Science or related field * Strong Python proficiency for ML and production systems * Solid software engineering fundamentals, system design, and design patterns * Hands-on experience with at least one major cloud platform (GCP, Azure, AWS) * Experience building and deploying production-grade ML systems * Strong communication skills to explain technical concepts to diverse stakeholders * Excellent time management, collaboration, and organizational skills Key requirements * Employee Assistance Program * Health, life, disability insurance * Retirement plans * Paid Time Off (PTO) and holidays * Equity may be offered * Paid vacations and holidays


## Related Videos

- [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning)
- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills)
- [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models)
- [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops)

## Related Articles

- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)