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# Machine Learning Engineer

- **Company:** Lever, Inc.
- **Location:** Lehi, UT, United States
- **Experience:** Expert
- **Salary:** $144,000.0 - $233,100.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Distributed Computing Environment, Python (Programming Language), Machine Learning, Performance Tuning, Software Engineering, Pytorch, Large Language Models, Deep Learning, Information Technology, Machine Learning Operations, Data Pipelines
- **Published:** August 26, 2026
- **Apply:** https://jobs.lever.co/entrata/d579bade-723d-4429-a1cb-565d15f3dff7/apply

## About the Role

* 5+ years of software engineering or machine learning engineering experience.
 * Hands-on experience fine-tuning, adapting, or deploying large language models.
 * Strong proficiency with Python and PyTorch or similar deep learning frameworks.
 * Experience building ML data pipelines, training workflows, and evaluation systems.
 * Experience deploying machine learning models into production environments.
 * Familiarity with modern LLM tooling, model serving, and inference frameworks.
 * Strong understanding of machine learning fundamentals and model performance tradeoffs., * Experience with supervised fine-tuning, preference optimization, or related post-training techniques.
 * Experience building agentic systems, tool-using models, or retrieval-based AI applications.
 * Experience with distributed training or GPU-based model workloads.
 * Familiarity with frameworks such as vLLM, DeepSpeed, FSDP, or similar technologies.
 * Experience working with enterprise or domain-specific AI applications.
 * Bachelor's or advanced degree in Computer Science, Machine Learning, Engineering, or a related field, or equivalent practical experience.

## Description

* Fine-tune and adapt large language models for Entrata-specific use cases using supervised fine-tuning and other post-training techniques.
 * Build scalable data preparation, curation, filtering, and synthetic data pipelines to support model training and evaluation.
 * Develop agentic AI systems that can reason across multi-step workflows, use tools, retrieve context, and operate reliably in production.
 * Build evaluation frameworks and benchmarks to measure model quality, safety, reliability, and task performance.
 * Optimize model inference, serving, and deployment for performance, cost, and scalability.
 * Partner with engineering, product, and data teams to integrate AI capabilities into Entrata products and workflows.
 * Help establish best practices for model experimentation, fine-tuning, evaluation, and deployment.


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- [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery)
- [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models)

## Related Articles

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