McBride
Data Science & AI: Data Scientist / AI Engineer
McBride, Norfolk, Virginia, United States, 23500
Overview
McBride has an exciting opportunity to support Allied Command Transformation (ACT), NATO’s leading agent for change: driving, facilitating, and advocating continuous improvement of Alliance capabilities to maintain and enhance military relevance and effectiveness. ACT leads concept development, capability development, training, and lessons learned initiatives and provides military support to policy development within NATO. Responsibilities
Contribute to the development and implementation of an enabling data science and AI capability at HQ SACT and across the NATO Enterprise, with a focus on scalable data engineering and software systems to support AI initiatives. Design, develop, and maintain data pipelines and architectures to manage ingestion, transformation, and processing of structured and unstructured data for large Language Model (LLM)-based applications and other AI systems. Lead efforts to optimize data delivery and automate data engineering processes, proposing infrastructure enhancements to improve scalability, efficiency, and reliability in support of LLM deployments. Build API-based infrastructure and frameworks enabling seamless integration of LLMs and ML models with operational systems, ensuring performance, security, and interoperability with NATO environments. Support the development, testing, and validation of microservices and containerized applications to operationalize AI/ML capabilities, including deployment of LLM use cases within NATO. Implement distributed data storage and processing systems (cloud-based or hybrid) that align with NATO standards and enable scalable use of LLMs across the enterprise. Develop tools and systems to improve data accessibility, enabling data scientists and analysts to efficiently interact with and query data for training, inference, and analytics. Coordinate with data scientists, software engineers, and system architects to align data engineering workflows with broader AI/ML objectives, ensuring timely delivery of clean, high-quality data for LLM training and inference. Establish mechanisms for real-time data processing and streaming to enable LLMs to operate effectively in dynamic applications such as operational decision support or strategic analysis. Conduct preprocessing, cleansing, and transformation of raw data into formats optimized for training, fine-tuning, and inference within LLM infrastructure. Implement robust monitoring, logging, and performance optimization tools for data pipelines and APIs, ensuring reliability and traceability of LLM-enabled workflows. Collaborate with teams to support federated learning approaches and cross-domain data sharing, ensuring compliance with NATO data sovereignty, security, and ethical guidelines. Provide subject matter expertise on data engineering and software development to military and civilian staff within HQ SACT or the NATO Enterprise, and develop proofs of concept for LLM-based applications as directed. Research, recommend, and implement best practices for deploying LLMs in secure, cloud-based environments such as Microsoft Azure or AWS, considering NATO-specific data policies and standards. Evaluate operational requirements and objectives, recommending appropriate engineering solutions for integrating LLMs into NATO workflows and systems. Stay abreast of new developments in AI engineering, including innovations in LLM technologies, data architectures, distributed computing, and API development, to bring cutting-edge capabilities into implementation within NATO. Provide technical training and mentoring to NATO staff, supporting educational efforts in AI engineering, data pipeline design, API development, and digital literacy. Foster a culture of innovation and data-driven decision-making across NATO by building scalable systems that enable effective exploitation of LLMs and advanced analytics. Perform additional tasks as required by the Contracting Officer’s Technical Representative (COTR) related to the LABOR category. Qualifications
Desired Qualifications Experience leveraging open-source frameworks and publicly available datasets to develop innovative AI and data engineering solutions for operational or analytical use cases. Proficiency in presenting data-driven insights clearly to non-technical audiences, showing the ability to craft compelling narratives and actionable recommendations for senior leadership. Understanding of military staff workflows and processes, along with familiarity with federated learning techniques for secure collaboration across NATO nations while preserving sovereignty of sensitive datasets. Exposure to agile project management methods and tools (e.g., Loop, JIRA, Trello) for coordinating and tracking progress across multi-disciplinary AI/ML projects. Exposure to cross-domain data sharing and API-driven interoperability, ensuring effective integration across systems while adhering to security and ethical guidelines within military or international environments. Familiarity with principles of ethical AI development, including bias mitigation, responsible data handling, and alignment with NATO’s ethical frameworks for AI deployment. Mandatory Qualifications Minimum 4 years of proven work experience as a Data Scientist, Machine Learning Engineer, Data Engineer, or Software Engineer, with emphasis on distributed systems, cloud-based architectures, developing operational AI/ML solutions, and designing API-based infrastructures, microservices architectures, and containerized applications (e.g., Docker, Kubernetes). Demonstrated experience working with GenAI, in particular LLMs, including preprocessing data, fine-tuning, and deployment in secure and scalable environments with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Proven expertise in programming languages such as Python, Java, or Scala, with experience in software engineering practices (version control, CI/CD pipelines, containerization). Experience building and optimizing data pipelines, ETL processes, and real-time streaming solutions using tools like Apache Airflow, Kafka, Spark, or equivalents. Knowledge of applied AI principles, particularly in implementing AI systems for operational decision support and analyzing unstructured data (text, imagery). Ability to architect and maintain scalable data lakes, data warehouses, or distributed storage systems (e.g., Delta Lake, Snowflake, Hadoop, or NoSQL solutions). Demonstrated understanding of data security, privacy, and sovereignty issues, particularly in military or international environments, ensuring compliance with NATO standards. Experience building visually impactful reports, dashboards, and analytics using tools such as Tableau, MS Power BI, or Kibana, supporting informed decision-making for high-level stakeholders. Professional experience in NATO environments or familiarity with NATO processes, organizational culture, and decision-making structures. Ability to translate operational problems into practical AI/ML solutions for military and civilian teams. Proven ability to collaborate within multidisciplinary teams, including coordinating with data scientists, software engineers, and system architects on cross-functional projects. Strong oral and written communication skills, with the ability to brief non-technical audiences and mentor staff in AI engineering, data science, and software development concepts. Seniorities and Employment
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Business Consulting and Services Note: This description omits boilerplate and site-specific notices and focuses on role responsibilities and qualifications.
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McBride has an exciting opportunity to support Allied Command Transformation (ACT), NATO’s leading agent for change: driving, facilitating, and advocating continuous improvement of Alliance capabilities to maintain and enhance military relevance and effectiveness. ACT leads concept development, capability development, training, and lessons learned initiatives and provides military support to policy development within NATO. Responsibilities
Contribute to the development and implementation of an enabling data science and AI capability at HQ SACT and across the NATO Enterprise, with a focus on scalable data engineering and software systems to support AI initiatives. Design, develop, and maintain data pipelines and architectures to manage ingestion, transformation, and processing of structured and unstructured data for large Language Model (LLM)-based applications and other AI systems. Lead efforts to optimize data delivery and automate data engineering processes, proposing infrastructure enhancements to improve scalability, efficiency, and reliability in support of LLM deployments. Build API-based infrastructure and frameworks enabling seamless integration of LLMs and ML models with operational systems, ensuring performance, security, and interoperability with NATO environments. Support the development, testing, and validation of microservices and containerized applications to operationalize AI/ML capabilities, including deployment of LLM use cases within NATO. Implement distributed data storage and processing systems (cloud-based or hybrid) that align with NATO standards and enable scalable use of LLMs across the enterprise. Develop tools and systems to improve data accessibility, enabling data scientists and analysts to efficiently interact with and query data for training, inference, and analytics. Coordinate with data scientists, software engineers, and system architects to align data engineering workflows with broader AI/ML objectives, ensuring timely delivery of clean, high-quality data for LLM training and inference. Establish mechanisms for real-time data processing and streaming to enable LLMs to operate effectively in dynamic applications such as operational decision support or strategic analysis. Conduct preprocessing, cleansing, and transformation of raw data into formats optimized for training, fine-tuning, and inference within LLM infrastructure. Implement robust monitoring, logging, and performance optimization tools for data pipelines and APIs, ensuring reliability and traceability of LLM-enabled workflows. Collaborate with teams to support federated learning approaches and cross-domain data sharing, ensuring compliance with NATO data sovereignty, security, and ethical guidelines. Provide subject matter expertise on data engineering and software development to military and civilian staff within HQ SACT or the NATO Enterprise, and develop proofs of concept for LLM-based applications as directed. Research, recommend, and implement best practices for deploying LLMs in secure, cloud-based environments such as Microsoft Azure or AWS, considering NATO-specific data policies and standards. Evaluate operational requirements and objectives, recommending appropriate engineering solutions for integrating LLMs into NATO workflows and systems. Stay abreast of new developments in AI engineering, including innovations in LLM technologies, data architectures, distributed computing, and API development, to bring cutting-edge capabilities into implementation within NATO. Provide technical training and mentoring to NATO staff, supporting educational efforts in AI engineering, data pipeline design, API development, and digital literacy. Foster a culture of innovation and data-driven decision-making across NATO by building scalable systems that enable effective exploitation of LLMs and advanced analytics. Perform additional tasks as required by the Contracting Officer’s Technical Representative (COTR) related to the LABOR category. Qualifications
Desired Qualifications Experience leveraging open-source frameworks and publicly available datasets to develop innovative AI and data engineering solutions for operational or analytical use cases. Proficiency in presenting data-driven insights clearly to non-technical audiences, showing the ability to craft compelling narratives and actionable recommendations for senior leadership. Understanding of military staff workflows and processes, along with familiarity with federated learning techniques for secure collaboration across NATO nations while preserving sovereignty of sensitive datasets. Exposure to agile project management methods and tools (e.g., Loop, JIRA, Trello) for coordinating and tracking progress across multi-disciplinary AI/ML projects. Exposure to cross-domain data sharing and API-driven interoperability, ensuring effective integration across systems while adhering to security and ethical guidelines within military or international environments. Familiarity with principles of ethical AI development, including bias mitigation, responsible data handling, and alignment with NATO’s ethical frameworks for AI deployment. Mandatory Qualifications Minimum 4 years of proven work experience as a Data Scientist, Machine Learning Engineer, Data Engineer, or Software Engineer, with emphasis on distributed systems, cloud-based architectures, developing operational AI/ML solutions, and designing API-based infrastructures, microservices architectures, and containerized applications (e.g., Docker, Kubernetes). Demonstrated experience working with GenAI, in particular LLMs, including preprocessing data, fine-tuning, and deployment in secure and scalable environments with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Proven expertise in programming languages such as Python, Java, or Scala, with experience in software engineering practices (version control, CI/CD pipelines, containerization). Experience building and optimizing data pipelines, ETL processes, and real-time streaming solutions using tools like Apache Airflow, Kafka, Spark, or equivalents. Knowledge of applied AI principles, particularly in implementing AI systems for operational decision support and analyzing unstructured data (text, imagery). Ability to architect and maintain scalable data lakes, data warehouses, or distributed storage systems (e.g., Delta Lake, Snowflake, Hadoop, or NoSQL solutions). Demonstrated understanding of data security, privacy, and sovereignty issues, particularly in military or international environments, ensuring compliance with NATO standards. Experience building visually impactful reports, dashboards, and analytics using tools such as Tableau, MS Power BI, or Kibana, supporting informed decision-making for high-level stakeholders. Professional experience in NATO environments or familiarity with NATO processes, organizational culture, and decision-making structures. Ability to translate operational problems into practical AI/ML solutions for military and civilian teams. Proven ability to collaborate within multidisciplinary teams, including coordinating with data scientists, software engineers, and system architects on cross-functional projects. Strong oral and written communication skills, with the ability to brief non-technical audiences and mentor staff in AI engineering, data science, and software development concepts. Seniorities and Employment
Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Business Consulting and Services Note: This description omits boilerplate and site-specific notices and focuses on role responsibilities and qualifications.
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