Top Machine Learning Jobs in Baltimore, MD

Design, build, and operate high-throughput, low-latency ad-serving infrastructure processing millions of requests per second. Optimize GPU-powered TensorRT inference, feature stores, model serving, benchmarking, experimentation tooling, and system reliability. Partner with machine learning engineers to productionize models and own systems through design, deployment, observability, capacity planning, incident response, and optimization.

Principal Data Scientist supporting a U.S. Government customer by designing and implementing machine learning, data mining, statistical analysis, AI, and advanced analytics solutions. The role requires analyzing complex datasets, developing predictive and prescriptive models, using Python or R and database technologies, and providing technical expertise for mission-critical software and systems. It is based in Annapolis Junction with limited partial telework and requires an active or reinstatable TS/SCI with Polygraph clearance.

Designs, develops, tests, and productizes scalable AI/ML algorithms and models. Responsibilities include model architecture, data pipeline integration, metrics analysis, deployment, scheduling, monitoring, retraining, and iterative improvement. The engineer will support mission-critical government systems, apply software engineering and model evaluation practices, communicate with customers, and potentially lead geographically distributed teams. The role requires advanced machine learning expertise, strong analytical and communication skills, U.S. citizenship, and an active or reinstatable TS/SCI with Polygraph clearance.

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 end-to-end LLM inference performance across serving systems, models, GPU hardware, and workloads. Define rigorous benchmarks, diagnose bottlenecks from scheduling through kernels and interconnects, optimize single- and multi-node deployments, and deliver production-ready runtimes and configurations. Collaborate with product and infrastructure teams, evaluate inference technologies, and implement runtime fixes. The role requires strong Python engineering, production experience with serving engines such as vLLM or SGLang, GPU profiling, and knowledge of modern inference optimization techniques.

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.

Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.

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.