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# ML Engineer

- **Company:** Karsun Solutions
- **Location:** Los Angeles, CA, United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** Training Data, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software as a Service, Information Systems, Data Governance, Python (Programming Language), Machine Learning, Platform as a Service (PAAS), Tensorflow, Azure Machine Learning, Salesforce.Com, Systems Integration, Pega, Enterprise Software Applications, Pytorch, Appian, Scikit Learn, Information Technology, No-code Tools, Machine Learning Operations, Mulesoft
- **Published:** October 28, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/88718116/1

## About the Role

* Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Operations Research, or a related field, plus a minimum of 7 years of relevant experience. 10 years of relevant experience may substitute for the degree.
 * Demonstrated experience designing, deploying, and maintaining machine learning models and pipelines in production enterprise environments.
 * Ability to obtain and maintain a VA Public Trust background investigation.
 * Available on contract award and willing to sign a letter of commitment., * Experience with MLOps tooling and model lifecycle management in a commercial cloud environment, such as AWS SageMaker or Azure Machine Learning.
 * Experience with ML in healthcare, benefits, or other regulated environments, including FedRAMP or ATO processes.
 * Proficiency in Python and common ML frameworks, such as PyTorch, TensorFlow, or scikit-learn.
 * Experience with data governance and responsible AI practices., Applicants must be authorized to work in the U.S.

## Description

Karsun Solutions is actively looking to support a modernization of digital services and accelerate delivery of healthcare and benefits programs for Veterans at the Department of Veterans Affairs. Candidates will support a program focused on expanding the Digital Transformation Center's ability to deliver enterprise applications using modern development frameworks, low code and no code platforms, and cloud based SaaS and PaaS environments. The objective is to deliver digital capabilities that support both Veteran healthcare services and benefits programs.

The program supports multiple concurrent low code/no code products serving a wide-range of users, while maintaining reliability, security, and delivery speed across a complex enterprise platform environment.

This position is a contingent opportunity. Prefer candidates local to the DMV Area and willing to be onsite two days per week.

What You'll Be Doing:

 * Design, develop, deploy, and maintain scalable machine learning models and pipelines that support enterprise mission objectives and operational baselines.
 * Apply advanced ML frameworks and lifecycle management practices to improve predictive capability, automation, and analytical insight, aligned with business requirements and data governance.
 * Lead model integration with the DTC enterprise platforms (Salesforce/MuleSoft, Microsoft Power Platform/Dynamics, Pega, Box, Appian) through APIs and reusable components.
 * Lead model performance monitoring, including drift detection, retraining, and validation, so solutions stay reliable and compliant after deployment.
 * Protect PII and PHI in training data and model outputs under HIPAA and VA privacy requirements, and support security and ATO documentation for ML components.
 * Educate stakeholders and provide technical guidance so solutions are delivered on schedule., At Karsun, we are committed to a fair and equitable hiring process. We do not use artificial intelligence to make decisions on candidates, scan resumes, or source potential hires. Applicants are reviewed by our talent acquisition team and hiring managers to ensure a thorough evaluation based on skills, experience, and alignment with our company values. Our hiring decisions are made with human judgement, ensuring fairness and transparency throughout the process.