Top Remote Machine Learning Jobs in Baltimore, MD

The role involves leading ML strategy, architecting systems, designing algorithms, collaborating with teams, and mentoring engineers in AI for enterprise analytics.

This role involves developing and integrating AI/ML models within GCP using Python, optimizing LLM performance, and applying MLOps practices. Strong collaboration with architects is required for implementation and analysis of workflows.

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The role involves designing and maintaining backend systems for ML applications, working closely with cross-functional teams, and optimizing AWS services.

The Principal AI/ML Platform Engineer leads the development and delivery of ML and GenAI platforms, ensuring scalability, compliance, and performance across various workflows and products, while mentoring the engineering team.

Own and execute the billing, financial, and corporate systems product roadmap. Define end-to-end experiences, lead 1-2 scrum teams, prioritize work using qualitative and quantitative data, and collaborate across Finance, Receivables, HR, analytics, UX and commercial teams to deliver automated, data-driven solutions that improve billing and financial functions.

The Data Scientist II will design and deploy ML models for autonomous vehicles, enhance data tagging, and improve dataset quality through advanced techniques and frameworks.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

The Senior ML/AI Engineer designs and implements ML/AI solutions, leading end-to-end ML/AI pipelines, collaborating with teams, mentoring, and developing infrastructure for large-scale data-driven products.

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

As a Machine Learning Engineering Intern at Airbnb, you will drive an AI-focused project, collaborate across teams, and contribute to search relevance and personalization initiatives.

As an AI Specialist SC, you will support major global clients by offering presales machine learning solutions, driving business transformations and technical discussions, while collaborating across teams.

The Senior Principal AI/ML Architect will drive AI architectural vision, influence multi-squad strategy, design intelligent systems, and set operational standards for Yahoo Mail's AI capabilities.

This role involves utilizing predictive analytics to develop customer retention strategies using advanced modeling techniques, data processing, and real-time interventions to improve user experience and business profitability.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

The Specialist Solutions Architect will design production-grade ML & AI applications, optimize AI workloads, and provide technical support while collaborating across teams to enhance Databricks' offerings.

The Lead ML Ops Data Scientist will design scalable MLOps systems, mentor data scientists, and develop models for rental matching and personalization.

The Senior Machine Learning Engineer will manage the lifecycle of ML models, transform prototypes to production code, build training pipelines, and monitor system performance.

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

The Software Engineer will develop machine learning infrastructure, optimize models, and create tools for data analysis while collaborating with a diverse team.

As a Senior Machine Learning Engineer, you will develop and deploy AI-driven products to enhance clinical trials, collaborating with teams to improve patient care through scalable machine learning solutions.