Top Senior Machine Learning Jobs in Baltimore, MD

As a Staff Machine Learning Research Scientist, you will lead ML research, develop evaluation frameworks, mentor researchers, and collaborate on clinical AI solutions.

Responsible for fine-tuning state-of-the-art LLMs, optimizing models for deployment, and driving AI architectural decisions. Collaborate with cross-functional teams to develop impactful AI products.

As a Senior ML Engineer for Payments, you will develop AI solutions for payment experiences, optimize transaction processing, and ensure system reliability while mentoring teammates and collaborating with cross-functional teams.

The Senior Analyst in Predictive Analytics and Machine Learning develops and maintains statistical models to support business decisions, monitors model performance, and collaborates with stakeholders across the company.

Lead a team of machine learning data scientists, overseeing model development for fraud detection and risk assessment, and ensuring quality throughout the model lifecycle while mentoring the team.

Design, build, and scale ML and Generative AI systems. Develop applications using ML architectures and monitor model performance.

The Staff Machine Learning Engineer will lead ML initiatives, develop AI systems, optimize pipelines, and mentor team members to automate healthcare processes.

Lead the design and operation of Twilio's ML and data platform, architecting cloud-native pipelines and implementing MLOps best practices while mentoring engineers and collaborating across teams.

The Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

As a Senior Machine Learning Scientist, you will design, build, and optimize deep learning models for biological data analysis, ensuring high-quality outputs and leading complex projects from conception through deployment.

The Senior Machine Learning Engineer will manage the full ML lifecycle, collaborating with teams to develop scalable systems that improve product decisions and empower monetization strategies.

As a Senior Machine Learning Engineer, you will develop and deploy ML models for health data analysis, collaborating with cross-functional teams to ensure reliability and regulatory compliance.

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

The role involves leading ML client engagements, shaping strategies, advising on ML architecture, and influencing project outcomes, while guiding teams and driving business value.

Lead the development of a robotics data platform, focusing on data enablement, API architecture, and mentoring engineers in complex system designs.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

The AI/ML Engineering Manager leads a team of ML engineers and architects, managing hiring, performance, and customer engagements while providing technical guidance in ML operations and architecture.

Design and implement production-grade ML systems for ICS/OT cybersecurity, build and optimize models (including NLP/LLMs), develop data pipelines and MLOps workflows, collaborate with data teams to deploy and monitor models in cloud and on-prem containerized environments, and troubleshoot production performance and resource issues.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.