Top Remote Machine Learning Jobs in Washington, DC

The Technical Product Manager will define roadmaps for an AI Platform, manage ML systems, partner with engineers, and improve healthcare outcomes.

The role involves leading strategic AI partnerships, driving revenue growth, and managing cross-functional teams while advocating for AI initiatives internally and externally.

The Manager, Growth Analytics & Marketing Science will build and evolve marketing measurement frameworks, drive analytics, and optimize marketing strategies through data and AI.

Lead a team optimizing backend systems for Netflix's Member Experience Pages. Focus on performance, scalability, architecture, and team growth while collaborating with various stakeholders.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

As a Quantitative Researcher, you'll develop strategies using alternative datasets to improve investment decisions, design and backtest models, and collaborate across teams to scale research into quant products.

The Senior Product Manager will lead the pricing and valuation engine, overseeing ML modeling, pricing systems, and improving valuation accuracy while managing cross-functional roadmaps and execution.

Lead the advancement of embedding-based retrieval systems, focusing on multimodal models, model performance, and extensibility for various use cases.

The Principal Applied Scientist will lead the development of advanced computer vision and ML systems, optimizing solutions for real-time performance on edge devices and ensuring reliability in dynamic environments.

The VP of Client Development will lead InMobi's growth strategy within the OEM and Telco sectors, establishing executive partnerships, joint business plans, and aligning product innovation to maximize market opportunities. The role requires extensive experience in enterprise partnerships and strategic business development with global technology leaders.

Co-found and lead a stealth startup building an agentic AI platform embedded in CAD tools to automate geometry updates, feature-tree edits, and cross-tool workflows. Drive product, engineering, and commercial strategy, hire the founding team, and develop a defensible data capture and automation stack for industrial CAD workflows.

Lead RWE study design and execution: develop protocols, statistical analysis plans, and R/SQL programs to produce analysis-ready datasets, tables, and figures; apply causal inference, time-to-event, and predictive methods; collaborate with scientists and stakeholders to deliver RWE insights.

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 developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

Design and implement machine learning bidding algorithms, evaluate their performance with large-scale data, and align them with business goals.

The Senior Machine Learning Engineer will design and implement detection systems to improve email security, lead project execution, and mentor junior engineers.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Lead Machine Learning Scientist designs and develops ML solutions, leads project teams, mentors members, and collaborates with clients to solve complex problems.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Data Scientist will analyze and model data related to ad-tier members, focusing on identity modeling and improving ad targeting capabilities, while collaborating with cross-functional teams.

Lead the strategic direction of data science at Mission Lane, innovating machine learning applications and managing a high-performing team to enhance financial outcomes.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

This role involves defining and managing the AI platform's roadmap, collaborating with cross-functional teams to integrate AI capabilities, and ensuring product quality and reliability metrics.