Top Senior Machine Learning Jobs in Washington, DC

The Senior Machine Learning Engineer will evaluate and apply advanced ML models, integrate with company infrastructure, and support data pipeline orchestration while focusing on autonomous vehicle technology.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

The Customer Success Engineer will act as a technical expert and advisor, ensuring customers adopt Deepgram's voice technologies effectively, manage customer relationships, conduct demos, and drive growth opportunities.

The Principal Product Manager will lead the Underwriting team to improve credit risk models, manage vendor relationships, and analyze portfolio performance.

Lead AI initiatives and governance, enhance AI capabilities, and develop internal training programs while collaborating across teams.

Lead analytical projects to optimize loan portfolio and pricing strategies, develop machine learning models, and collaborate across teams to drive growth.

Lead the design strategy for Pluralsight's analytics experience, translating complex data into actionable insights while mentoring designers and fostering collaboration across teams.

Manage global technical support teams for MongoDB, focusing on customer satisfaction through technical issue resolution, performance enhancement, and team development.

The Engineering Manager will lead the Payments Risk engineering strategy, mentor the team, provide technical leadership, and collaborate across departments to ensure effective risk management solutions are developed for the organization.

The Senior Staff Software Engineer will design and implement risk platform architecture, mentor team members, and manage project priorities to mitigate financial threats and improve detection of user patterns.

The Staff Machine Learning Engineer will define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

The Staff Machine Learning Engineer will utilize AI models, mentor team members, and enhance automation solutions across Coinbase's operations, focusing on machine learning to solve complex challenges.

As a Senior Staff Engineer at Coinbase, you will improve incentives infrastructure, drive growth, and solve complex technical problems in cryptocurrency applications.

As a Risk Manager, you'll analyze and mitigate security risks, implement fraud defenses, and collaborate with cross-functional teams to enhance security objectives.

The role involves leading and scaling the Risk AI/ML team, managing multiple teams, and owning end-to-end ML systems to mitigate fraud and risk at Coinbase.

As a Senior Product Manager in Risk Enablement at Coinbase, you'll define strategies, prioritize roadmaps, and lead cross-functional teams to develop scalable risk management systems, ensuring compliance and enhancing customer security.

The Machine Learning Engineer will deploy models, improve existing systems, collaborate with teams, and work with large datasets for government clients.

Research Engineer will develop and optimize machine learning algorithms for defense applications, focusing on edge devices and enhancing autonomy for military systems.

As a Senior Forward-Deployed Engineer, you'll integrate solutions for customers, design technical architectures, debug issues, and contribute to product development with a focus on customer success.

Lead the AI transformation at Unanet, developing strategies, governance frameworks, and overseeing AI solution implementation for business efficiency.

As a Senior Staff Software Engineer, you will design scalable infrastructure for ML models, optimize performance, and collaborate with teams to enhance ML experimentation tools.

The AI Product Sales Manager drives sales in AI products through strategic planning, managing sales pipelines, and collaborating with partners and teams to exceed quotas.

Lead GenAI/AI initiatives by collaborating with cross-functional teams to identify opportunities, ensure ethical practices, and develop scalable solutions. Communicate effectively with stakeholders and support successful project transitions into products.

The Engagement Manager manages project execution, collaborates with technical teams on AI solutions, develops client relationships, and coaches consultants.

Lead the development of ML-powered personalization systems, managing a team of engineers and ML practitioners to drive technical roadmap and collaboration for effective borrower experiences.