Top Machine Learning Jobs in Baltimore, MD

Develop and sustain mission-critical government software and systems using Java, Python, and AWS. Implement functional and system-level automated tests, prototype cloud-based solutions, and collaborate with systems engineers within an Agile development process. The role requires U.S. citizenship and an active or reinstatable TS/SCI with Polygraph clearance.

Develop and sustain mission-critical software and systems for a U.S. Government customer. Apply Python and related technologies including Kotlin/Java, Terraform, Elasticsearch/OpenSearch, and AWS. Collaborate independently and within engineering teams while supporting reliable software solutions, Agile development, and mission-focused technical initiatives. The role requires a TS/SCI with Polygraph clearance and is based in Annapolis Junction with partial telework available after acclimation and training.

Own BI product management for Quote-to-Cash and Order-to-Cash financial systems. Partner with finance, sales, legal, product, and engineering teams to identify operational friction, define BI and AI/ML opportunities, author PRDs and roadmaps, and ensure quoting, contracting, billing, and revenue recognition data is accurately represented in downstream products.

Design, create, and implement AI and ML systems for Defense and Intelligence sectors, ensuring scalability and integration into various environments.

Designs end-to-end dataflow plans, including ingestion, transformation, security boundary crossings, and destination endpoints. Resolves complex routing problems independently, researches unfamiliar systems, adapts standard operating procedures, and documents repeatable technical solutions. Uses Confluence and Jira to track workflows, team progress, documentation gaps, and routing anomalies while supporting critical U.S. Government mission systems.

Develop machine learning, statistical, graph-based, and data-mining algorithms for national-security missions. Build, optimize, and validate AI/ML and large language models; create feature vectors, experiments, simulations, visualizations, and predictive analytics; and implement prototypes in production frameworks. Collaborate with subject-matter experts to automate analysis, guide analytic development, and deliver data-driven insights. Experience with LLMs, RAG, agents, GPU computing, and active TS/SCI clearance with polygraph is required.

Supports AI/ML teams by curating image and video datasets, managing annotation workflows, running model training and evaluation jobs, maintaining benchmarks, documenting results, and analyzing model failures with senior engineers. The role requires foundational Python, machine learning, computer vision, cloud, and data-quality skills, with opportunities to grow into applied modeling or MLOps.

Develops and deploys AI and machine learning models, algorithms, and analytics for federal customers. Responsibilities include analyzing datasets, testing and refining models, developing statistical and graph-based algorithms, creating visualizations, automating manual analysis, and integrating prototype solutions into production analyst workflows. Requires quantitative education, extensive data analysis and programming experience, and a TS/SCI clearance with polygraph.

Build and productionize traditional machine learning models, owning feature engineering, validation, deployment, monitoring, drift detection, and retraining. Develop LLM-powered agentic tools, dashboards, self-serve analytics products, and automated insight pipelines. Partner with engineering and business stakeholders, write production-grade Python and SQL, drive adoption, improve data quality, and establish responsible AI workflows for a regulated industry.

Lead offensive cyberspace operational planning for USCYBERCOM-related missions. Develop and synchronize offensive and defensive cyber plans, targeting activities, operational orders, courses of action, intelligence support, and crisis plans. Coordinate Joint Operational Planning Groups, integrate cyber capabilities, assess threats, and support execution across Department of Defense and Intelligence Community partners. The role requires extensive cyber operations planning experience, deep knowledge of cyber threats and military planning processes, and an active TS/SCI clearance with polygraph.

Lead malware analysis, reverse engineering, digital forensics, incident response, threat intelligence, and cyber threat assessments supporting USCYBERCOM. Analyze compromised systems, media, logs, malware, adversary TTPs, and intelligence data; develop indicators and signatures; produce technical reports and leadership briefings; support incident response policies, operational planning, risk assessments, and cyber situational awareness. The role requires collaboration across cyber and intelligence organizations and an active Top Secret clearance with SCI eligibility and polygraph.

Own and improve Headway’s privacy program across HIPAA, 42 CFR Part 2, state privacy laws, individual rights, incidents, vendor governance, and AI use. Maintain controls, data maps, metrics, training, and operational workflows. Conduct product, vendor, and AI privacy assessments; manage rights requests and incident investigations; coordinate notifications and regulatory submissions; and translate complex requirements into practical guidance for cross-functional teams.

Own the strategy and roadmap for patient-provider search, retrieval, ranking, and marketplace matching. Lead experimentation, objective functions, evaluation, and ML platform foundations while partnering with ML engineers, data scientists, design, clinical teams, and executives. Improve successful, lasting care matches rather than optimizing only clicks or bookings. Balance patient access, provider growth, clinical quality, and payer priorities, while setting the standard for technically grounded product management.

Develop autonomy evaluation metrics, statistical and machine-learning analyses, dashboards, and pipelines for simulation and on-road autonomous vehicle testing. Analyze perception, prediction, and planning performance; identify anomalous behavior and critical scenarios; apply VLMs and LLMs where appropriate; and support release gating and safety decisions. The role requires production Python, C++ debugging, technical leadership, cross-functional collaboration, and rigorous software engineering practices.

Define architecture and metrics for autonomous driving evaluation, lead cross-functional integration across autonomy and simulation teams, develop statistical and machine learning methods, analyze large-scale time-series data, manage evaluation KPIs and release gates, and communicate safety and readiness insights through dashboards and stakeholder presentations.

Serves as the technical bridge between customers, Sales, and technology teams. Leads technical discovery, solution architecture, demonstrations, workshops, proofs of concept, and evaluations using HERE data, APIs, mapping, routing, spatial analytics, cloud, AI, and enterprise integration. Partners with Sales to qualify opportunities, reduce technical risk, develop proposals and reusable presales assets, and guide customers toward location-intelligence solutions.

Analyze malware, binary files, customer detection tickets, and machine learning detections to improve detection efficacy and reduce false positives. Review product detections, assess binary legitimacy, address internal detection questions, and provide insights to data science teams. The role collaborates with technical account managers, incident response teams, data scientists, and malware researchers. Required capabilities include malware analysis, reverse engineering, Python scripting, binary fundamentals, threat assessment, research methods, operating systems, and AI-assisted workflow improvement.

Develop full-stack web applications integrating AI, machine learning, and computer vision models. Build and test software using Java, Spring Boot, Python, React, MongoDB, and Docker; collaborate with data science teams, customers, and stakeholders; enhance the company website; and contribute to products throughout their lifecycles.

Build and own full-stack web applications connecting AI/ML capabilities with intelligence customers. Responsibilities include developing CMO’s website and workflow tools, collaborating with computer vision and data science engineers, prototyping new capabilities, engaging stakeholders and users, and testing and deploying software throughout its lifecycle.

Develop end-to-end applications that help mission analysts access and interpret complex data. Collaborate with stakeholders, data scientists, and analysts to translate operational needs into enterprise solutions. Build front-end interfaces, back-end services, APIs, and integrations with data repositories. Use Python, Java, JavaScript, PySpark, Elasticsearch, and distributed data processing, with opportunities to integrate machine learning, artificial intelligence, and generative AI technologies.

Develops and sustains cloud software supporting cyber intelligence and AI/ML capabilities on large-scale compute clusters and AWS infrastructure. Responsibilities include requirements analysis, software development, integration, testing, validation, installation, enhancement, maintenance, and issue resolution. The role works with distributed NoSQL systems, big-data technologies, cloud scalability, machine learning, large language models, RAG, agentic workflows, microservices, Kubernetes, observability, and infrastructure-as-code tools.

Analyze complex structured and unstructured datasets, develop statistical and machine learning models, build data pipelines, and create visualizations supporting mission and business decisions. The role requires strong Python-based analytics, data wrangling, database management, data quality practices, and stakeholder collaboration. Candidates must have an active TS/SCI with polygraph, a bachelor’s degree, and at least five years of relevant experience.

Develop and deploy end-to-end applications supporting intelligence mission workflows. Responsibilities include gathering requirements, building user-facing applications, developing RESTful APIs, integrating front-end and back-end services, creating data visualizations, working with cloud environments and data repositories, and establishing secure CI/CD pipelines. The role collaborates with mission stakeholders, data scientists, and analysts to deliver operational solutions.

Designs, trains, evaluates, and deploys AI/ML and deep learning models for mission-critical applications. Analyzes complex datasets, develops predictive algorithms, integrates models into operational systems, and supports testing, validation, deployment, and lifecycle management. Collaborates with engineers, data scientists, and mission stakeholders; documents AI/ML initiatives; researches emerging technologies; and may support LLM, generative AI, NLP, cloud, distributed computing, and MLOps capabilities.

Develop and evaluate machine learning and statistical models supporting intelligence analysis. Curate, transform, and integrate data; build classifiers and anomaly detection systems; deploy and refine models in production; monitor model performance and data accuracy; collaborate with analysts and software developers; document processes and datasets; and communicate findings to stakeholders.