Top Remote Machine Learning Jobs in Washington, DC

The Senior Director of Data Science & AI leads AI strategy execution, managing a multidisciplinary team to develop and govern AI solutions, with a focus on innovation, operations, and ethical standards.

The Senior Engineer will evaluate ML subsystems for autonomous vehicles, setting performance metrics and ensuring safety through data analysis and coordination with teams.

The AI Sales Executive drives new business growth and expands client relationships by selling AI-driven solutions for engineering and manufacturing sectors, managing the full sales cycle with a consultative approach.

As a Senior Technical Product Manager, you will lead the AI Platform team to define roadmaps, collaborate with technical experts, and improve healthcare delivery by leveraging AI technologies.

As a Staff Full-Stack Engineer, you will manage end-to-end experiments, build full-stack product experiences, and drive product and technology experiments with various teams.

Lead product strategy for Arcadia's Utility Data Platform, managing Senior PMs, developing product features, and ensuring successful delivery for enterprise customers.

The AI & Data Science Director will lead AI strategies, foster technical leadership, support team development, and integrate generative AI into products.

The Senior Machine Learning Engineer will develop high-performance services, innovate ad technologies, and collaborate with teams to optimize ad campaigns through AI and ML solutions.

Lead and grow the AI Forward Deployed Engineering team, oversee customer AI/ML transformations, and develop strategic partnerships while managing key accounts.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

As a QA Engineer, you'll validate features, handle bug fixes, leverage AI for QA workflows, and enhance test automation across multiple product teams.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

As Head of Product, you will define the product vision and execute strategy for an AI-driven logistics billing platform, focusing on customer discovery, AI integration, and team leadership.

The Director of Adversary Engineering will define strategies for log management and security automation, lead the development of automated workflows, and optimize security systems using AI/ML techniques.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.

Develop and deploy end-to-end machine learning solutions, collaborate with cross-functional teams, and implement MLOps frameworks while monitoring model performance in production.

The Brand Marketing Manager will develop content strategies for lead generation, produce high-quality marketing assets, collaborate with the Demand Generation team, and analyze data to optimize campaigns.

The Product Marketing Manager will execute product launches and support go-to-market initiatives, collaborating with cross-functional teams to develop and deliver messaging and enablement materials targeting both technical and business stakeholders.

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.

Lead product strategy and development in cybersecurity, focusing on supply chain security solutions. Engage with customers and cross-functional teams to drive product innovation and performance metrics.

The GTM role focuses on increasing revenue through new sales and partnerships, understanding client needs, and communicating product value.

The Data Science Actuary role involves building and maintaining rating systems and risk models, conducting analysis for underwriting and operations, and integrating new data sources while collaborating with multiple teams.