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# Machine Learning Engineer

- **Company:** Robotics Technologies LLC
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Code Review, Computer Programming, Data Governance, Python (Programming Language), Machine Learning, NumPy, Recommender Systems, Tensorflow, Standard Sql, Management of Software Versions, Feature Engineering, Data Ingestion, Pytorch, Apache Spark, Model Validation, Pandas, Scikit Learn, Kubernetes, Integration Frameworks, Machine Learning Operations, Restful APIs, Docker
- **Published:** June 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=067c51b537d2790a

## About the Role

Do you have experience in Statistics?, * 6-11 years of overall experience with strong focus on Machine Learning Engineering

 * Strong programming experience in Python
 * Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn
 * Experience with data processing frameworks (Spark, Pandas, NumPy)
 * Strong understanding of ML algorithms, statistics, and model evaluation techniques
 * Experience deploying models using REST APIs, Docker, Kubernetes
 * Solid knowledge of SQL and working with large databases
 * Experience with cloud platforms (AWS, Azure, or GCP)
 * Strong problem-solving and communication skills, * Prior experience working with financial services or banking clients
 * Experience with NLP, Time Series, or Recommendation Systems
 * Exposure to CI/CD pipelines and automation tools
 * Knowledge of data governance and model risk management

## Description

* Design, develop, and deploy scalable Machine Learning models for real-world business problems
 * Work with large-scale structured and unstructured datasets
 * Build and maintain end-to-end ML pipelines (data ingestion, feature engineering, model training, evaluation, and deployment)
 * Collaborate closely with Data Engineers, Data Scientists, and Product teams
 * Optimize model performance, accuracy, and efficiency
 * Implement MLOps best practices including monitoring, versioning, and retraining
 * Ensure compliance with security, governance, and regulatory standards
 * Participate in code reviews, design discussions, and technical documentation


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