Job description

Location: Springfield, VA Experience Level: Senior Level Clearance: Active TS/SCI with CI Polygraph Required Salary Range: $120,000 – $185,000 annually (Based on skills and experience) At Data Machines, we leverage data analytics, DevSecOps, machine intelligence, and data science to engineer innovative solutions for our Federal Government, Department of Defense, and commercial customers. Our teams solve complex, mission-critical challenges using modern technology and secure engineering practices. We are seeking an experienced Senior Applied AI/ML Engineer to develop end-to-end data engineering, analytics, and machine learning capabilities in an agile, fast-paced customer environment supporting Special Operations missions. You will work as part of a small, multidisciplinary team to build scalable data pipelines, develop and deploy machine learning models, and deliver reliable, analyst-facing applications and tools. The ideal candidate combines strong data engineering fundamentals with applied data science and software development expertise. You will contribute across the full lifecycle of a solution, from ingesting and transforming large-scale datasets to developing models, building APIs, deploying production services, and delivering practical tools directly to mission users. This position will be performed on-site at a customer location in Northern Virginia. Minimum Qualifications Active TS/SCI security clearance with a CI polygraph. U.S. citizenship required. Bachelor’s degree in Computer Science, Data Science, Information Science, Mathematics, Statistics, Engineering, or a related field. 8+ years of related experience in data engineering, data science, machine learning engineering, software engineering, or a combination of these disciplines. Strong programming experience with Python, PySpark, and SQL. Experience designing, developing, and optimizing production data pipelines that process large-scale or complex datasets. Experience developing and deploying analytics, machine learning, or data-intensive applications and services. Experience with data modeling, ETL/ELT processes, data quality, transformation logic, and analytical or search-oriented data stores. Ability to translate ambiguous mission requirements and customer challenges into practical data, analytics, and software solutions. Strong collaboration, communication, analytical, and problem-solving skills. Ability to work independently, take initiative, and collaborate effectively with customers, analysts, software engineers, and technical leadership. Ability to work on-site at a customer location in Northern Virginia. Preferred Qualifications Experience with distributed data engineering technologies, including Apache Spark/PySpark, HDFS, Delta Lake, Elasticsearch, or similar platforms. Experience deploying and operating machine learning models and inference services at scale across GPU/CPU clusters or containerized environments. Experience with advanced analytics, including geospatial analysis, H3 indexing, graph analytics, computer vision, optical character recognition (OCR), natural language processing (NLP), or large language models (LLMs). Experience developing analyst-facing data and machine learning applications using FastAPI, Django, React, TypeScript, or similar technologies. Experience with cloud platforms, including AWS, Azure, or OpenStack. Experience with DevOps, containerization, and orchestration tools such as Docker, Nomad, Kubernetes, GitLab, CI/CD pipelines, or Ansible. Experience building APIs and production services using FastAPI, Django, Java, or equivalent frameworks. Experience integrating machine learning capabilities into operational workflows and mission-focused applications. Experience working in Agile development environments supporting Department of Defense or other Federal Government customers. Ability to troubleshoot, optimize, and maintain scalable data pipelines, machine learning services, and production applications. Key Responsibilities Design, develop, and maintain scalable data pipelines to ingest, transform, process, and deliver large-scale and complex datasets. Build end-to-end data engineering and machine learning capabilities that support Special Operations mission requirements. Apply advanced analytics, statistical methods, and machine learning techniques to solve complex operational problems. Develop, deploy, and maintain machine learning models, inference services, and data-intensive applications in production environments. Build and integrate APIs and backend services that expose data, analytics, and machine learning capabilities to mission users. Develop analyst-facing applications and tools that make complex data and analytical results accessible and actionable. Implement data modeling, ETL/ELT workflows, data quality controls, and transformation logic to ensure reliable data products. Optimize data processing workflows and distributed computing environments for performance, scalability, and reliability. Collaborate with analysts, software engineers, data scientists, customers, and technical leadership to translate mission needs into effective technical solutions. Evaluate and implement appropriate technologies, frameworks, and architectures to support evolving customer requirements. Troubleshoot and resolve issues related to data pipelines, model performance, application functionality, and production services. Participate in Agile planning, technical reviews, testing, deployment, and continuous improvement activities. Support the development and operation of secure, reliable, and scalable solutions in a mission-focused customer environment. This position requires an active U.S. Government security clearance. Applicants who do not currently hold the required clearance and CI polygraph will not be eligible for consideration. Employment is contingent upon verification of clearance status. This position is contingent upon contract award. APPLY NOW Culture: Smart People, No Red Tape Data Machines does not discriminate in employment, services, and activities on the basis of race, color, religion, national origin, sex, gender identity, sexual orientation, pregnancy, childbirth or related medical conditions, age, marital status, veteran status, disability, or any other basis prohibited by law. Data Machines invites any applicant to review the Data Machines’ written Affirmative Action Plan, available for inspection during the hiring process. Our salary ranges are market-driven and set to allow for flexibility. Individual pay will be competitive based on a candidate’s unique set of knowledge, skills, and geographic diversity, with earnings potential commensurate with experience. Apply Now <div class="elementor-element elementor-element-5564b2e3 ob-has-background-overlay elementor-widget elem

Requirements

Must-haves

Location: Springfield, VA
Experience Level: Senior Level
Clearance: Active TS/SCI with CI Polygraph Required
This position will be performed on-site at a customer location in Northern Virginia.
Active TS/SCI security clearance with a CI polygraph.
U.S. citizenship required.
Bachelor’s degree in Computer Science, Data Science, Information Science, Mathematics, Statistics, Engineering, or a related field.
8+ years of related experience in data engineering, data science, machine learning engineering, software engineering, or a combination of these disciplines.
Strong programming experience with Python, PySpark, and SQL.
Experience designing, developing, and optimizing production data pipelines that process large-scale or complex datasets.
Experience developing and deploying analytics, machine learning, or data-intensive applications and services.
Experience with data modeling, ETL/ELT processes, data quality, transformation logic, and analytical or search-oriented data stores.
Ability to translate ambiguous mission requirements and customer challenges into practical data, analytics, and software solutions.
Strong collaboration, communication, analytical, and problem-solving skills.

Nice-to-haves

Experience with distributed data engineering technologies, including Apache Spark/PySpark, HDFS, Delta Lake, Elasticsearch, or similar platforms.
Experience deploying and operating machine learning models and inference services at scale across GPU/CPU clusters or containerized environments.
Experience with advanced analytics, including geospatial analysis, H3 indexing, graph analytics, computer vision, optical character recognition (OCR), natural language processing (NLP), or large language models (LLMs).
Experience developing analyst-facing data and machine learning applications using FastAPI, Django, React, TypeScript, or similar technologies.
Experience with cloud platforms, including AWS, Azure, or OpenStack.
Experience with DevOps, containerization, and orchestration tools such as Docker, Nomad, Kubernetes, GitLab, CI/CD pipelines, or Ansible.
Experience building APIs and production services using FastAPI, Django, Java, or equivalent frameworks.
Experience integrating machine learning capabilities into operational workflows and mission-focused applications.
Experience working in Agile development environments supporting Department of Defense or other Federal Government customers.
Ability to troubleshoot, optimize, and maintain scalable data pipelines, machine learning services, and production applications.

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aimlmachine learningagilepythonsqlreacttypescriptawsazuredockerkubernetesci/cdjava

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