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Junior Machine Learning Engineer
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Junior Machine Learning Engineer
- Melbourne, Florida, United States
- Melbourne, Florida, United States
À propos
ENSCO, Inc. is seeking a Junior Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks, architectures, pipelines, and advanced data analytics, to address difficult problem sets. Work closely with other senior scientist to understand problem sets, physical data feature sets and parameters. The successful candidate must have demonstrated understanding of signal processing, data fusion, feature extraction, and be able to apply it towards ML and DL solutions. Assess algorithm performance of features by building datasets and designing and executing well-controlled experiments. ENSCO's Mission Systems Group (MSG) provides innovative customized products and services vital to national safety and security. A primary focus area is the development of advanced algorithm development and integration for multipurpose data sets.
Qualifications Required: * Bachelors degree in Machine Learning, Data Science, Mathematics, or equivalent in a related discipline. Direct relevant military experience will also be considered. * Minimum of 2 years related industry experience in machine learning, data science, and analytics. * Proven track record of successful data science and algorithm implementation. * A self-starter with excellent oral and written communication skills. * Experience navigating and programming within the Linux environment. * Experience working with structured and unstructured databases. * Advanced proficiency with data science languages (e.g. Python, Matlab,) * Demonstrated experience with Deep Learning frameworks (e.g. PyTorch, TensorFlow/Keras, scikit-learn, MXNet). * Experience working with large data sets and ability to extract relevant information from data sets. * The ability to obtain and maintain a US security clearance is required for this position, for which you must be a U.S. Citizen
Qualifications Desired: * Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent. * Experience with ML/DL algorithms extracting signal from noise. * Past experience being able to develop solutions using disparate data sets through ML techniques. * DevOps experience involving CI/CD pipelines to build and deploy. * Experience working with container orchestration technologies (e.g. Docker/Kubernetes). * An Active TS/SCI clearance.
Work Location Type: Hybrid Required Certifications: None U.S. Citizenship Required: Yes Security Clearance Required: Ability to obtain Employment Type: Regular Full-time Background Check Type: 7 Year Pre-Employment Drug Screen Required: None Position Contingent Upon Contract Award: Yes
Salary Range $65,499.20—$106,620.80 USD REAL ID Requirement This position may require the ability to access to U.S. federal facilities. In accordance with the Department of Homeland Security's enforcement of the REAL ID Act, as of May 7, 2025, individuals must present a REAL ID-compliant form of identification or an acceptable alternative to gain entry. For a list of acceptable forms of identification, please click here. Benefits At ENSCO, a positive working environment and a competitive salary are only part of the reason for choosing a career here. We offer a comprehensive benefits package that creates a stimulating and supportive environment where you can thrive - visitensco.com/careers/benefits to learn more. Export Control and Licensing This position may involve access to technology or technical data that is controlled under U.S. export control laws and regulations and the release of which to a non US person may require an export license from the U.S. Government. Privacy Your data privacy is important to ENSCO. Please click here to view our privacy policy. California residents can click here to view your California privacy rights. EEO Statement ENSCO, Inc. and its wholly owned U.S. subsidiaries are Equal Opportunity Employers- veterans, disability
Compétences linguistiques
- English
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