Machine Learning (ML) Engineer

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    "requisitionDescription": "<div><div><div><div><div><div><div><div><p><img src=\"https://static.workforcenow.adp.com/cccustom/Client/Recruitment/velocityx-logo-horizontal_3520b319-e666-486b-8e98-5201905f200d.png\" style=\"width: 300px;\" class=\"fr-fic fr-dib fr-fil\"></p><p><strong>About Velocity-X:</strong><br>Velocity-X, a VelocityBlack company, constructs and deploys data management and analytics solutions for the defense and intelligence communities. We&rsquo;re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission&rsquo;s biggest challenges.</p><p id=\"isPasted\">Velocity-X 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.</p><p><strong>Responsibilities:</strong></p><ul><li>Design, develop, and implement machine learning models and algorithms to solve specific business problems.</li><li>Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.</li><li>Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.</li><li>Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.</li><li>Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.</li><li>Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.</li><li>Monitor and maintain deployed models, ensuring their reliability and performance in production environments.</li><li>Troubleshoot and resolve issues related to machine learning models and pipelines.</li><li>Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.</li><li>Contribute to the development of best practices and standards for machine learning development and deployment within the team.</li><li>Document machine learning models, experiments, and deployment processes.</li><li>Potentially work with large datasets and big data technologies.</li><li>Optimize machine learning models for performance and efficiency.</li></ul><p><strong>Qualifications:</strong></p><ul><li>Master&rsquo;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.</li><li>Demonstrated hands-on&nbsp;experience in developing and deploying machine learning models in a production environment.</li><li>Strong programming skills in Python and&nbsp;experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn,&nbsp;etc.</li><li>Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures).</li><li>Experience with data preprocessing, feature engineering, and data visualization techniques.</li><li>Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).</li><li>Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.</li><li>Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.</li><li>Strong&nbsp;analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.</li><li>Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.<strong>&nbsp;</strong></li></ul><p><strong>Preferred Skills:</strong></p><ul><li>Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.</li><li>Experience with MLOps practices and tools for automating and monitoring machine learning workflows.</li><li>Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.</li><li>Experience with building and deploying RESTful APIs.</li><li>Familiarity with big data technologies and distributed computing.</li><li>Experience with statistical modeling and inference.&nbsp;</li></ul><p><strong>Position Clearance Requirement:</strong></p><p>TS/SCI with Full-Scope Polygraph</p><p><strong>Equal Opportunity Employer:</strong>&nbsp;</p><p>Velocity-X is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.</p></div></div></div></div></div></div></div></div>\n",
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