Machine Learning Engineer
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At a glance
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Job overview
Insight Global is hiring a Machine Learning Engineer. One of our largest Telecom customers is seeking a Machine Learning / Research Engineer to support the research, development, and enhancement of advanced location intelligence capabilities powered by proprietary cellular network and cell site data. The individual will apply machine learning, data engineering, and software development expertise to improve accuracy, scalability, and quality of location‑based solutions for fraud detection, public safety, customer insights, and marketing analytics.
Key focus areas include Apply machine learning, data engineering, and software development expertise to improve accuracy, scalability, and quality of location‑based solutions., Conduct research, experimentation, and implementation of advanced analytical techniques for real‑world use cases., and Build and deploy machine learning models in production environments..
Important skills include Machine Learning Development, Data Engineering, Large-Scale Data Processing, Python, Feature Engineering, and Research Experimentation.
Skills & qualifications
Skills
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Full job description
Job Description
One of our largest Telecom customers is seeking a Machine Learning / Research Engineer to support the research, development, and enhancement of advanced location intelligence capabilities powered by proprietary cellular network and cell site data. This individual will apply machine learning, data engineering, and software development expertise to improve the accuracy, scalability, and quality of location-based solutions that support critical business functions such as fraud detection, public safety initiatives, customer insights, and marketing analytics. The ideal candidate has a strong Computer Science, Computer Engineering, or related STEM background, experience building and deploying machine learning models in production environments, and a proven track record of solving complex real-world problems using large-scale data. Candidates should be comfortable working throughout the full development lifecycle, from research and experimentation to implementation and optimization, while collaborating with cross-functional teams to deliver innovative data-driven solutions. The ideal candidate has a Master's degree in computer science / engineering and has prior industry or applied research experience.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Skills and Requirements
-Strong hands-on machine learning development experience designing, training, evaluating, and deploying machine learning models in production environments.
-Data engineering & large-scale data processing experience building data pipelines & working with large, complex datasets, including data ingestion, transformation, feature engineering, and optimization.
-Strong proficiency in Python and experience developing scalable, production-quality software solutions supporting machine learning & analytics initiatives.
-Master's degree in computer science with a demonstrated experience applying research, experimentation, and advanced analytical techniques to real-world use cases. -Experience working with cellular network, geospatial, or location-based datasets
-Experience supporting fraud detection, public safety, or marketing analytics use cases
-Published thesis work, research, patents, or industry innovation projects.
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