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# Lead Machine Learning Engineer

- **Company:** Kforce Inc.
- **Location:** Armonk, NY, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Continuous Integration, Information Engineering, Dataspaces, Github, Python (Programming Language), Machine Learning, Operational Data Store, Recommender Systems, Azure Machine Learning, Software Deployment, Systems Architecture, Sql Optimization, Pytorch, Snowflake, Pandas, Containerization, Scikit Learn, Optimization Algorithms, Xgboost, Performance Monitor, Machine Learning Operations, Software Version Control, Docker
- **Published:** August 5, 2026
- **Apply:** https://www.dice.com/job-detail/61aca0bc-3062-4887-a5c2-08408c1a0a85

## About the Role

* 8+ years of experience in Machine Learning Engineering, Data Engineering, or AI solution development
 * Proven experience designing enterprise-scale machine learning architectures and deploying production ML solutions
 * Strong Python development experience including pandas, scikit-learn, XGBoost/LightGBM, and PyTorch (preferred)
 * Advanced SQL skills with experience working in Snowflake
 * Hands-on experience with Azure Machine Learning, GitHub, and Docker
 * Strong understanding of MLOps, model deployment, monitoring, and lifecycle management
 * Experience leading technical teams and delivering enterprise analytics solutions, * Experience with optimization algorithms, operations research, or resource planning
 * Experience within the Energy and Utilities industry or another regulated environment
 * Familiarity with enterprise operational data platforms and utility data ecosystems
 * Strong communication skills with the ability to bridge business needs and technical solutions

## Description

Kforce has a client in Armonk, NY that is seeking a Lead Machine Learning Engineer to support a leading Energy and Utilities organization by designing and delivering scalable machine learning solutions that drive operational efficiency and business decision-making. This role will own the end-to-end machine learning architecture, lead the design of predictive models and recommendation engines, and guide models from prototype through production deployment., * Design and own the overall machine learning system architecture and model lifecycle

 * Develop scalable predictive models and recommendation engines to support operational and resource planning initiatives
 * Lead technical design decisions and mentor small delivery teams throughout the development lifecycle
 * Translate business requirements into machine learning solutions and production-ready models
 * Partner with data engineers, data scientists, and business stakeholders to deliver high-impact analytics solutions
 * Deploy, monitor, and optimize machine learning models using Azure Machine Learning
 * Establish best practices for model governance, performance monitoring, and continuous improvement
 * Maintain CI/CD workflows, version control, and containerized deployments using GitHub and Docker


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