Top Remote Machine Learning Jobs in Washington DC
Senior Machine Learning Modeler role at Cash App's Financial Crimes Technology team. Responsible for building ML models to detect illegal activity, improve agent workflow, and facilitate ML-based Customer Risk Rating program. Must have 4+ years of ML modeling experience.
Kensho is seeking Machine Learning Engineer interns to work on ML systems, conduct research, design scalable models, and collaborate with a cross-functional team. Flexibility to work remotely within the U.S. but may require travel to Kensho hubs like Cambridge, MA or NYC. Salary range of $120k - $130k with additional incentives and equity plans.
Looking for an ML Engineer specializing in constructing and managing robust, scalable, and high-performance compute platforms tailored for ML workflows. Collaborating closely with scientists to ensure efficient model training and integration into production environment. Responsible for reliability, cost-effectiveness, scalability, and velocity of ML models.
Looking for an ML Engineer to construct and manage robust, scalable, and high-performance compute platforms for ML workflows. Responsible for ensuring efficient model training and integration into production, supporting autonomous vehicles at Cruise. Must have strong problem-solving skills and a bias towards action.
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Seeking an experienced AI and Automation Strategist to analyze and automate processes using AI technologies in the cybersecurity domain. Responsibilities include developing automation strategies, integrating AI solutions, implementing solutions with IT teams, and monitoring performance for business growth and efficiency improvement.
Seeking an experienced AI and Automation Strategist to analyze and apply AI to security processes, drive efficiency, and improve productivity. Responsibilities include analyzing processes, developing automation strategies, integrating AI, and overseeing implementation for operational and financial impact. Required skills include cybersecurity leadership, automation and AI solution implementation, knowledge of programming languages, and experience in the pharmaceutical industry.
Experience in quality assurance and application development, strong test automation skills in Java and Python, testing large-scale production systems, evaluating AI/ML models, creating comprehensive test plans, and collaborating with developers to design testing strategies for features being developed.
The Manager of Machine Learning Engineering at Samsara leads teams in building and managing machine learning solutions for customers, focusing on computer vision, sensor fusion, and AI deployment. This role is fully remote in the US and Canada, with a focus on impactful technology development for industries like transportation and manufacturing.
Seeking a skilled MLOps Engineer to spearhead model deployments for Computer Vision and Machine Learning. Responsibilities include designing and implementing MLOps pipelines, managing the lifecycle of models, optimizing cloud infrastructure, collaborating with the team, and staying updated on industry trends.
Design, build, and manage distributed services and pipelines for Underwriting & Credit at Cash App. Lead cross-team projects, ensure high code quality, collaborate with various teams, and contribute to development capabilities through mentoring.
As a Generative AI Scientist at Mission Cloud, you will leverage generative AI models to build internal products, collaborate with teams, and contribute to groundbreaking AI solutions. Responsibilities include designing and deploying AI models, collaborating with interdisciplinary teams, and staying updated on AI trends. Requirements include experience in AI model implementation, programming skills in Python and AI frameworks, and AWS certifications. This remote position offers a rewarding package and career development opportunities.
Design, develop, and program methods, processes, and systems to analyze big data sources and generate actionable insights. Collaborate with product and service teams to identify questions and issues for data analysis and experiments. Develop software programs, algorithms, and automated processes to cleanse and evaluate large datasets. Communicate insights and findings to stakeholders.
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