Top Machine Learning Jobs in Baltimore, MD

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

Drive delivery excellence and customer success by leading the architecture and implementation of AI/ML solutions while ensuring account growth and client engagement.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

The Staff ML Platform Engineer will enhance Afresh's ML platform performance and scalability, collaborating with ML teams to improve systems and deploy models efficiently.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

The Director of Data Engineering, ML & AI leads data strategy and AI capabilities, managing a team to enhance data infrastructure, machine learning systems, and sustainability analytics while driving company-wide AI initiatives.

The Machine Learning Engineer will develop and enhance search and retrieval systems, adapting search behaviors and integrating ML models for product recommendations, while managing infrastructure and data processing.

The Senior Machine Learning Engineer will build and enhance models and systems for classifying and enriching Internet data, collaborating with various teams to improve data quality and insights.

Lead the development and deployment of ML models to optimize pricing and enhance customer experiences. Drive AI strategies, conduct research, and collaborate across teams.

The Enterprise Account Executive drives growth through AI and ML SaaS solutions in the food and beverage industry, managing complex sales cycles and building relationships with key stakeholders.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.

As a Software Engineer in ML Infrastructure, you will develop scalable data pipelines, enhance data discovery, and collaborate with teams on data organization and ML features.

Senior ML research leader who translates state-of-the-art ML pipeline insights into product requirements, reference architectures, benchmarks, and platform roadmaps. Partners cross-functionally and with strategic customers and research institutions to set evaluation standards, reproducibility, and responsible ML practices while providing technical leadership and influencing product and executive audiences.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

The role involves designing and supporting GPU/Kubernetes clusters for AI/ML workloads, developing automation tools, and troubleshooting infrastructure issues.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.