{"schemaVersion":"jobsearcher.job.v1","id":"2aa794c80804b815bfce5c7e","url":"https://jobsearcher.com/jobs/2aa794c80804b815bfce5c7e","canonicalUrl":"https://jobsearcher.com/jobs/2aa794c80804b815bfce5c7e","title":"Machine Learning Engineer","description":"Data Science & AI InnovationMachine Learning EngineerRichmond, VAFull TimeRole Details for Machine Learning EngineerAbout The Machine Learning Engineer RoleKey Responsibilities Design and implement scalable machine learning models and pipelines Work with large-scale datasets to develop classification, regression, NLP, and time series forecasting solutions Collaborate with data engineers to ensure proper data collection, transformation, and feature engineering Deploy models to production using MLOps practices (Docker, CI/CD, model versioning) Conduct model performance evaluation, tuning, and retraining cycles Research and apply state-of-the-art techniques and open-source frameworks Communicate findings to stakeholders with clear visualizations and reports Support proposal development and client engagements involving AI/ML scopesKey Responsibilities for Machine Learning EngineerRequired Qualifications For Machine Learning EngineerMust-Have QualificationsBachelor’s or Master’s in Computer Science, Data Science, Machine Learning, or a related field3+ years of experience building and deploying ML models in productionProficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost)Strong understanding of data structures, algorithms, and statisticsExperience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes)Familiarity with MLOps tools (MLflow, SageMaker, Vertex AI, etc.)Excellent problem-solving, communication, and documentation skillsNice to HaveExperience with NLP frameworks (spaCy, Hugging Face Transformers)Familiarity with Spark or distributed ML frameworksPrior experience working on federal data science or analytics contractsKnowledge of data privacy and compliance (GDPR, HIPAA, FedRAMP)Why Machine Learning Engineer at Precise AnalyticsPrecise Analytics is a data engineering and AI firm headquartered in Richmond, VA. We deliver data engineering, business intelligence, and machine learning solutions to government and commercial clients — and we operate a specialized AI Workforce Solutions division that supplies skilled human contributors to leading AI training platforms. We are committed to building a technically excellent team.Precise Analytics is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, or any other characteristic protected by law.","company":"Precise Analytics","rawCompany":"precise analytics","city":"Henrico","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-06-23T11:42:05.498Z","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":"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"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"Data Science & AI InnovationMachine Learning EngineerRichmond, VAFull TimeRole Details for Machine Learning EngineerAbout The Machine Learning Engineer RoleKey Responsibilities Design and implement scalable machine learning models and pipelines Work with large-scale datasets to develop classification, regression, NLP, and time series forecasting solutions Collaborate with data engineers to ensure proper data collection, transformation, and feature engineering Deploy models to production using MLOps practices (Docker, CI/CD, model versioning) Conduct model performance evaluation, tuning, and retraining cycles Research and apply state-of-the-art techniques and open-source frameworks Communicate findings to stakeholders with clear visualizations and reports Support proposal development and client engagements involving AI/ML scopesKey Responsibilities for Machine Learning EngineerRequired Qualifications For Machine Learning EngineerMust-Have QualificationsBachelor’s or Master’s in Computer Science, Data Science, Machine Learning, or a related field3+ years of experience building and deploying ML models in productionProficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost)Strong understanding of data structures, algorithms, and statisticsExperience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes)Familiarity with MLOps tools (MLflow, SageMaker, Vertex AI, etc.)Excellent problem-solving, communication, and documentation skillsNice to HaveExperience with NLP frameworks (spaCy, Hugging Face Transformers)Familiarity with Spark or distributed ML frameworksPrior experience working on federal data science or analytics contractsKnowledge of data privacy and compliance (GDPR, HIPAA, FedRAMP)Why Machine Learning Engineer at Precise AnalyticsPrecise Analytics is a data engineering and AI firm headquartered in Richmond, VA. We deliver data engineering, business intelligence, and machine learning solutions to government and commercial clients — and we operate a specialized AI Workforce Solutions division that supplies skilled human contributors to leading AI training platforms. We are committed to building a technically excellent team.Precise Analytics is an equal opportunity employer. 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