Top Machine Learning Jobs in Baltimore, MD

The role involves providing expertise in Cyber Operations at a Joint Operations Center, developing SOPs, maintaining situational awareness, and facilitating communication and reporting for operational effectiveness.

Support Offensive Cyberspace Operational Planning for USCYBERCOM operations, develop plans, and coordinate cyber capabilities. Engage with operational teams and enhance situational awareness.

Analyze and assess malware threats for USCYBERCOM, leading forensic analysis, developing technical reports, and collaborating on threat detection and response.

As a Risk Manager, you'll analyze and mitigate security risks, implement fraud defenses, and collaborate with cross-functional teams to enhance security objectives.

The Head of Consumer Product will create engaging experiences using relational AI, focusing on user well-being rather than metrics like engagement. Responsibilities include product strategy, user research, gamification, and community building.

Lead a team of ML engineers to develop computer vision models, manage ML roadmaps, and improve product functionalities through innovative technologies.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

As a Target Digital Network Analyst, you will analyze collection data for insights, maintain databases, identify intelligence gaps, and collaborate with various teams on intelligence missions.

Lead the development and execution of ML platform strategies, manage a high-performing team, and enhance 3D deep learning applications.

The CND Analyst supports cyber discovery, defense against APTs, and utilizes machine learning for anomaly detection, preferably with extensive network security experience.

This role involves designing and building advanced ML models to protect against fraud and enhance user experience while mentoring lower-level engineers and influencing technical roadmaps.

The Senior Data Scientist will support U.S. government contracts by developing machine learning algorithms, conducting advanced data analysis, and leading a team of data scientists. Strong collaboration with software engineers and subject matter experts is essential to develop production analytics for mission-critical applications.

The role involves designing, developing, and deploying machine learning models for healthcare applications, collaborating with cross-functional teams, and optimizing model performance.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

The Image Processing Engineer develops algorithms to process and evaluate images, correcting optical anomalies and enhancing scientific image data, while leading technical writing and communication efforts.

As a Data Scientist at Wyetech, develop strategies for analyzing large datasets, communicate findings, and assist others in data-driven decision-making for federal clients. The role emphasizes mathematical and statistical modeling as well as programming skills.

The role involves leading Gartner's AI technology research, advising clients on AI applications, managing generative AI solutions, and providing actionable insights on AI trends and best practices.

The role involves producing insights for AI product management, advising clients on AI strategy, and developing business approaches for AI technologies. The analyst will work closely with executives and product managers, driving AI investments and guiding product lifecycle management.

The role involves advising on resource optimization, managing cross-training programs, and supporting JOC operations, while integrating cyber capabilities into operational plans.

The role involves leading the Revenue ML team, managing engineers focused on building AI/ML capabilities for user and revenue growth, overseeing project execution, and fostering collaboration among cross-functional teams.