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# Staff Machine Learning Engineer in Nationwide

- **Company:** Energy Jobline
- **Location:** Olathe, KS, United States (Remote available)
- **Experience:** Expert
- **Salary:** $100,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Memory Management, Python (Programming Language), Machine Learning, Software Deployment, Software Engineering, Pytorch, Delivery Pipeline, Backend, Low Latency, Production Code, Machine Learning Operations, Data Pipelines
- **Published:** July 11, 2026
- **Apply:** https://www.energyjobline.com/job/staff-machine-learning-engineer-nationwide-31120650

## About the Role

* Proven experience delivering machine learning systems into production.

 * Strong understanding of modern foundation models and large models.

 * Experience building scalable training and inference infrastructure.

 * Excellent software engineering skills with a focus on maintainable, production-quality code.

 * Comfortable leading technical delivery while remaining hands-on.

 * Strong communication skills and the ability to collaborate across research, engineering and product teams.

## Description

This is a senior hands-on leadership position where you'll own the execution of the company's machine learning platform, working closely with research, software engineering and product teams to build scalable, production-grade AI solutions.

Responsibilities

 * Own the end-to-end machine learning lifecycle, including data pipelines, model training, evaluation, inference and deployment.

 * Fine-tune and optimise large models using modern techniques such as LoRA, QLoRA, supervised fine-tuning, preference optimisation and model distillation.

 * Design scalable inference infrastructure with a focus on latency, reliability and operational efficiency.

 * Build and maintain high-quality data pipelines for both synthetic and real-world datasets.

 * Develop robust evaluation frameworks covering model quality, robustness, safety and performance.

 * Optimise GPU utilisation, memory usage and inference performance for production deployments.

 * Work closely with software engineers to integrate ML capabilities into backend services and customer-facing products.

 * Lead technical delivery, mentor engineers and help shape engineering best practices.

 * Balance research ambitions with practical engineering trade-offs to deliver value quickly.

Technology

 * Python

 * PyTorch and/or JAX

 * Large-scale GPU training and inference infrastructure

 * Modern ML deployment pipelines


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