Top Machine Learning Jobs in Washington, DC

Lead the enterprise-wide AI adoption initiative, managing strategies, budgets, and communications across departments while preparing executive presentations and mentoring successors.

This role focuses on optimizing large-scale financial modeling applications by implementing MLOps practices and maintaining end-to-end pipelines on AWS.

The role involves defining and building the company's machine learning capabilities, designing production ML systems, owning data strategy, and partnering with engineers. Requires experience in ML system production and software engineering fundamentals.

The Staff Machine Learning Engineer will define and build ML capabilities, design production systems, and lead ML strategy in a high-growth AI cybersecurity company.

The VP AI/Machine Learning will define and implement machine learning capabilities in a high-growth cybersecurity company, focusing on strategy, infrastructure, and building production systems. The role involves defining ML applications, data strategy, and mentoring an ML team.

The role involves defining and building ML capabilities, creating production systems, and managing data strategy while collaborating with engineers and leading an ML team.

Lead product strategy for data and AI solutions, drive analytics, manage integrations, and improve decision-making in health-tech.

The Solutions Architect aligns technology strategies with business objectives, leading solution design and architecture to deliver scalable IT solutions. Responsibilities include managing projects, evaluating technology trends, and driving efficiencies through AI and automation.

Lead and manage late-stage clinical trials for respiratory products. Build teams, develop strategies, and ensure compliance and collaboration across functions to drive execution in asthma and COPD programs.

Design and deploy AI/ML solutions for real-world problems, collaborating with teams to build, evaluate, and integrate models into production systems.

Summer internship for MS/PhD students to apply AI/ML and LLMs to clinical pharmacology datasets, perform literature review and data management, and develop/validate PBPK and PK/PD models using tools like R or Python.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

As a Staff Machine Learning Engineer, you will design and evaluate ML models, optimize performance, and work with stakeholders to deliver AI solutions.

As a Senior Machine Learning Engineer, develop LLM evaluation frameworks and agentic AI workflows to extract insights from conversations and optimize customer experiences.

The role involves delivering advanced analytics and machine learning solutions, collaborating with stakeholders, and mentoring junior data scientists.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

Seeking Applied Scientist to build scalable AI systems for estate planning, focusing on production-grade applications and document understanding using advanced AI models.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

The Senior Machine Learning Operations Engineer will build and operationalize the ML Ops platform to deploy and monitor machine learning models, focusing on infrastructure, automation, and integrating ML workloads within the AWS-native architecture.

Lead technical direction for AI across products, architect RAG services, mentor engineers, and ensure compliance in AI usage.

As a Senior Product Manager, you will lead the development of tools for financial advisors, focusing on product execution, advisor-centric development, and integrating AI into workflows while mentoring junior team members.

Lead initiatives in designing and building large-scale distributed data systems and ML infrastructure, while collaborating across various engineering teams.