Top Machine Learning Jobs in Baltimore, MD

The Director of AI/ML Engineering will lead and scale the AI/ML team, collaborating on innovative projects in machine learning, computer vision, and predictive algorithms. Responsibilities include mentoring team members, overseeing the ML lifecycle, and driving technical vision alongside senior leaders.

As a Senior Machine Learning Engineer in Risk AI/ML, you will lead model strategy and design sophisticated systems to prevent fraud while mentoring junior engineers.

Design and implement machine learning pipelines for fraud and payment systems, collaborating with data scientists and engineers to enhance reliability and decision-making.

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.

The Principal Product Manager will oversee AI/ML initiatives, drive product development, translate strategy into technical specs, and manage product lifecycle.

Lead Joint Cyberspace Operational planning within USCYBERCOM, providing expert guidance, drafting operational plans, and overseeing integration of cyber capabilities.

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.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.

The Software Engineer III will focus on leveraging Generative AI for patient solutions, enhancing voice AI agents, and managing technical projects while mentoring peers.

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 Senior Machine Learning Engineer, you will design, build, and deploy large-scale ML systems to enhance Dropbox's AI features, collaborating with teams and mentoring peers.

As a Machine Learning Intern, you will work on advanced AI solutions, collaborate with teams to design ML systems, and analyze data to enhance user experiences at Dropbox.

The role involves improving Python development workflows, leading projects across teams, mentoring engineers, and enhancing developer productivity using various tools and systems.

The role involves enhancing developer tools for GM's AV engineers, addressing pain points, and mentoring team members to improve productivity and maintain quality code efficiency.

As a Senior Staff Software Engineer, you will design scalable infrastructure for ML models, optimize performance, and collaborate with teams to enhance ML experimentation tools.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Design and develop edge AI firmware for camera systems, ensuring accurate AI algorithms, collaborating on architecture, and mentoring engineers.

The Principal Python Software Developer will transition functionalities, develop prototypes, create user query forms, and support operational maintenance in a government client environment.

The role involves building and optimizing ML platforms, mentoring engineers, ensuring low-latency infrastructure, and enhancing data quality for model performance.

Responsible for building globally distributed ML ecosystems, developing data pipelines, implementing microservices, and collaborating across teams to enhance machine learning technologies.

The role involves building awareness of technologies, mentoring talent, promoting a culture of engineering excellence, and collaborating on critical business issues.

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