Top Machine Learning Jobs in Baltimore, MD

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

Build a next-generation ML data and feature infrastructure platform to enhance the productivity of ML practitioners and improve feature accessibility.

Join Netflix's Algorithms team as a Machine Learning Software Engineer to design and develop solutions for personalization systems. Collaborate on scalable machine learning algorithms and enhance software engineering practices.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

The Staff Software Engineer will lead the design and architecture of the AI/ML platform, mentor engineers, and drive technical direction for MLOps infrastructure in healthcare automation.

Develop and deploy machine learning models for fraud detection and prevention, collaborating with teams and ensuring model performance over time.

The Senior Machine Learning Engineer will enhance fraud detection capabilities through ML technologies, improve model performance, and lead high-impact ML projects from experimentation to production.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

As a Product Manager, you'll transform data into opportunities, manage technical product development, and foster cross-functional collaboration for philanthropic initiatives.

As a Machine Learning Engineer, you'll build AI solutions from structured leadership data, develop RAG-based agents, and enhance the Leadership Intelligence Platform, focusing on efficiency and collaboration with research partners.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead the technical vision and architecture for machine learning and data systems, overseeing scalable infrastructure and collaboration across teams.

The Senior Machine Learning Engineer will design and implement ML solutions, collaborate with teams, and contribute to scalable infrastructure enhancements.

Seeking Applied Scientist to build scalable AI systems for estate planning, focusing on production-grade applications and document understanding using advanced AI models.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

Design and implement a perception system for autonomous vehicles, focusing on data integration from various sensors and ensuring safe operation.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

The role involves designing and developing machine learning infrastructure and models, consulting on best practices, and building scalable services for AI integration.

As a Senior Machine Learning Engineer, you will design ML infrastructure, build AI features, and collaborate with cross-functional teams while managing large data sets.

Develop and maintain web-based tools for AI/ML practitioners, improve model observability, enhance user experience, and collaborate cross-functionally. Drive product excellence and improve systems and codebase.

The role involves delivering advanced analytics and machine learning solutions, collaborating with stakeholders, and mentoring junior data scientists.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.