Top AI & Machine Learning Jobs

Leads the design and integration of enterprise GIS, AI, machine learning, and advanced analytics solutions. Develops spatial analyses, dashboards, predictive models, automation, data pipelines, and decision-support tools using ArcGIS and Python. Manages complex datasets, establishes data quality and AI governance standards, evaluates emerging technologies, and collaborates with technical and business stakeholders. Provides technical leadership, mentoring, troubleshooting, documentation, and project support.

Leads the integration of AI, generative AI, and RAG tools into federal proposal development. Develops AI workflows, prompt libraries, SOPs, compliance processes, and performance metrics; trains proposal teams on secure, human-reviewed AI usage; evaluates emerging GovCon tools; and drives productivity, quality, proposal cycle-time, and probability-of-win improvements while leading teams and managing direct reports.

Develop AI harnesses and agentic systems integrating AI/ML services, enterprise platforms, cloud infrastructure, and modern user interfaces. Build secure, distributed architectures; implement CI/CD, automated testing, performance and token optimization, and anti-hallucination controls. Collaborate with technical and executive stakeholders to deliver strategic systems, support rapid-cycle R&D, and improve engineering standards. The onsite McLean role includes occasional travel and requires eligibility for a security clearance, with TS/SCI preferred.

Own strategy, architecture, reliability, security, and lifecycle of the enterprise data and AI platform stack (Snowflake, Dataiku, Power BI, Semarchy, Collibra). Define roadmaps, establish engineering standards and guardrails, drive modernization (lakehouse, cloud-native, containerization), ensure resilience, observability, zero-trust data access, and governance. Lead platform engineering, SRE, vendor management, and influence cross-functional senior stakeholders in a regulated defense environment.

Own strategy, architecture, reliability, security, and lifecycle of the enterprise data and AI platform stack (Snowflake, Dataiku, Power BI, Semarchy, Collibra). Define roadmaps, engineering standards, and guardrails; drive modernization (lakehouse, cloud-native, containerization); ensure integration, observability, incident response, resiliency, and zero-trust data access. Lead and develop engineering, SRE, and platform operations teams; manage vendors, budgets, and influence senior stakeholders on platform investments and risks.

Design, develop, and deploy end-to-end machine learning and large language model solutions. Perform data discovery, cleaning, preprocessing, and visualization. Build/train LLMs and Agent+RAG systems, collaborate with stakeholders and AI teams, and apply graph-based analysis to support enterprise integration and analytics.

Perform data cleaning, preprocessing, integration, and quality assurance; create complex visualizations and dashboards (Tableau/Power BI); run routine data quality checks; and apply AI/ML models to analyze unstructured data to support mission-critical decision making.

Lead design and implementation of complex embedded and application software for signal processing and algorithm development (including machine learning) for EO/IR and electronic warfare systems. Provide technical leadership, mentor teams, produce design/project documentation, evaluate and optimize algorithms (C++), and collaborate with systems, hardware, and test engineers through full lifecycle development and customer technical reviews.