• Design, develop and support computer applications.
• Develop and direct software system testing and maintenance tasks.
• Build applications using various software tools and technologies such as MS SQL Server, SSIS, SSRS, VMWare, SAN, UNIX, .Net, JAVA, UI/UX, Oracle, Sales Force. Will work in unanticipated locations. Work under supervision.
• Will work in unanticipated locations. Work under supervision. Travel and/or Relocation to unanticipated Client sites throughout USA is required.

The candidate will be responsible for designing, developing, and deploying end-to-end machine learning models and scalable data pipelines. This role involves performing data analysis, feature engineering, model training, experimentation, and statistical evaluation to ensure high-quality model performance. The individual will deploy machine learning models into production environments using APIs and cloud platforms, continuously monitor and optimize model accuracy, reliability, and efficiency, and collaborate closely with cross-functional teams to deliver AI-driven solutions. Proper documentation of models, experiments, and workflows will be required to support long-term scalability and maintenance.

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Education Required

​A Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field is required, or equivalent practical experience.

Experience Required

The ideal candidate will have 3+ years of professional experience in machine learning, data science, or a related role. Strong programming skills in Python or R are required, along with hands-on experience using machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. The candidate should have practical experience working with Pandas, NumPy, and SQL, a solid understanding of machine learning algorithms and statistics, and experience deploying models on cloud platforms such as AWS, Azure, or Google Cloud Platform. Experience with Docker and Kubernetes is considered a plus.

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