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# Machine Learning Engineer

- **Company:** RECRUITER ON DECK, INC.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $75,000.0 - $120,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Data Cleansing, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, SQL Databases, Unstructured Data, Google Cloud, Feature Engineering, Pytorch, Deep Learning, Model Validation, Generative AI, Scikit Learn, Kubernetes, Information Technology, Data Analytics, Machine Learning Operations, Data Pipelines, Software Library, Docker
- **Published:** June 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f119c975697c8dbb

## About the Role

Do you have experience in Statistics?, Do you have a Bachelor's degree in statistics?, * Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related field.

 * Minimum of 3 years of professional experience in machine learning, data science, or a related role.
 * Proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.
 * Experience with SQL and working with structured and unstructured datasets.
 * Knowledge of machine learning algorithms, model evaluation techniques, and statistical analysis.
 * Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
 * Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

 * Experience with MLOps tools, Docker, Kubernetes, or CI/CD pipelines.
 * Knowledge of natural language processing, deep learning, or generative AI applications.
 * Experience deploying machine learning models into production environments.

## Description

We are seeking a Machine Learning Engineer to design, develop, and deploy scalable machine learning solutions that support business objectives. The ideal candidate will have experience building predictive models, working with large datasets, and collaborating with cross-functional teams to deliver data-driven products and insights., * Develop, train, evaluate, and optimize machine learning models for production environments.

 * Design and implement data preprocessing, feature engineering, and model validation workflows.
 * Build and maintain scalable data pipelines to support machine learning initiatives.
 * Deploy, monitor, and improve model performance using MLOps best practices.
 * Collaborate with software engineers, data analysts, and business stakeholders to translate requirements into technical solutions.
 * Conduct experiments and analyze results to identify opportunities for model improvement.
 * Create technical documentation and communicate findings to both technical and non-technical audiences.
 * Ensure data quality, model reliability, and adherence to organizational standards.


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