{"schemaVersion":"jobsearcher.job.v1","id":"9bbfc6130266225c1a0e974b","url":"https://jobsearcher.com/jobs/9bbfc6130266225c1a0e974b","canonicalUrl":"https://jobsearcher.com/jobs/9bbfc6130266225c1a0e974b","title":"Machine Learning Engineer","description":"Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We're proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission's biggest challenges.\nDark Wolf is seeking a highly motivated and self-directed professional to fill the role of Machine Learning (ML) Engineer to support our team in Northern Virginia.\nResponsibilities:\nDesign, develop, and implement machine learning models and algorithms to solve specific business problems.\nBuild and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.\nTransform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.\nCollaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.\nExperiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.\nEvaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.\nMonitor and maintain deployed models, ensuring their reliability and performance in production environments.\nTroubleshoot and resolve issues related to machine learning models and pipelines.\nStay up-to-date with the latest advancements in machine learning, deep learning, and related fields.\nContribute to the development of best practices and standards for machine learning development and deployment within the team.\nDocument machine learning models, experiments, and deployment processes.\nPotentially work with large datasets and big data technologies.\nOptimize machine learning models for performance and efficiency.\nQualifications:\nMaster's in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.\nDemonstrated hands-on experience in developing and deploying machine learning models in a production environment.\nStrong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.\nSolid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures).\nExperience with data preprocessing, feature engineering, and data visualization techniques.\nFamiliarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).\nExperience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.\nUnderstanding of software development principles, version control (e.g., Git), and CI/CD pipelines.\nStrong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.\nExcellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.\nPreferred Skills:\nExperience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.\nExperience with MLOps practices and tools for automating and monitoring machine learning workflows.\nKnowledge of containerization technologies like Docker and orchestration tools like Kubernetes.\nExperience with building and deploying RESTful APIs.\nFamiliarity with big data technologies and distributed computing.\nExperience with statistical modeling and inference.\nPosition Clearance Requirement:\nTS/SCI with Full-Scope Polygraph\nThis position is located in Chantilly/Herndon, VA.\nWe are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.\nIn compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.","company":"Darkwolfsolutions","rawCompany":"darkwolfsolutions","city":"Gaithersburg","state":"MD","isRemote":false,"isActive":false,"createdAt":"2026-08-05T11:55:33.926Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We're proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission's biggest challenges.\nDark Wolf is seeking a highly motivated and self-directed professional to fill the role of Machine Learning (ML) Engineer to support our team in Northern Virginia.\nResponsibilities:\nDesign, develop, and implement machine learning models and algorithms to solve specific business problems.\nBuild and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.\nTransform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.\nCollaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.\nExperiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.\nEvaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.\nMonitor and maintain deployed models, ensuring their reliability and performance in production environments.\nTroubleshoot and resolve issues related to machine learning models and pipelines.\nStay up-to-date with the latest advancements in machine learning, deep learning, and related fields.\nContribute to the development of best practices and standards for machine learning development and deployment within the team.\nDocument machine learning models, experiments, and deployment processes.\nPotentially work with large datasets and big data technologies.\nOptimize machine learning models for performance and efficiency.\nQualifications:\nMaster's in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.\nDemonstrated hands-on experience in developing and deploying machine learning models in a production environment.\nStrong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.\nSolid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures).\nExperience with data preprocessing, feature engineering, and data visualization techniques.\nFamiliarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).\nExperience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.\nUnderstanding of software development principles, version control (e.g., Git), and CI/CD pipelines.\nStrong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.\nExcellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.\nPreferred Skills:\nExperience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.\nExperience with MLOps practices and tools for automating and monitoring machine learning workflows.\nKnowledge of containerization technologies like Docker and orchestration tools like Kubernetes.\nExperience with building and deploying RESTful APIs.\nFamiliarity with big data technologies and distributed computing.\nExperience with statistical modeling and inference.\nPosition Clearance Requirement:\nTS/SCI with Full-Scope Polygraph\nThis position is located in Chantilly/Herndon, VA.\nWe are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.\nIn compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.","datePosted":"2026-08-05T11:55:33.926Z","dateModified":"2026-08-05T11:55:33.926Z","hiringOrganization":{"@type":"Organization","name":"Darkwolfsolutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Gaithersburg","addressRegion":"MD","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"9bbfc6130266225c1a0e974b"},"url":"https://jobsearcher.com/jobs/9bbfc6130266225c1a0e974b"}}