Top Remote Machine Learning Jobs in NYC, NY
Senior Manager overseeing ML projects from planning to delivery, driving long-term vision, and collaborating cross-functionally with AI/ML Engineers, Product Managers, Quality Engineers, Program Managers, Information Security Engineers, and Product Legal Counsels.
Senior ML Engineer role at Grammarly's On-Device ML team, responsible for proposing, designing, and prototyping new features, building ML models, integrating models into user interfaces, launching and monitoring model deployment, and staying updated with academic research.
Seeking a VP of Machine Learning Operations to lead the optimization and management of ML models in a production environment. Responsibilities include architecting ML frameworks, integrating models into operational pipelines, designing scalable ML pipelines, and optimizing performance and cost-efficiency of ML systems. Requires extensive experience with AWS, GCP, Python, ETL, large datasets, data science technologies, predictive analytics, and machine learning.
Featured Jobs
Join Enigma as a Senior Machine Learning Engineer to improve entity resolution algorithms, predict small business behavior, and develop machine learning infrastructure. Build ML systems and tools, collaborate with cross-functional teams, and impact decision-making in the small business economy.
As a Machine Learning Engineer at Dropbox, you will design, build, evaluate, deploy and iterate on large scale ML systems, work with cross-functional teams to personalize users' experiences, and contribute to revolutionizing collaboration tools. Requires 2+ years of ML or AI system building experience and strong analytical skills.
Join Spring Health as a Senior Machine Learning Engineer to contribute to the development of algorithms and datasets for personalized member care and data products. Responsibilities include building data-centric features, developing an AI platform, and monitoring deployed models. Success in this role involves launching new recommender system products, creating data products using GenerativeAI, and collaborating with data science teams.
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Lead data projects to launch new machine learning products and improve predictive features in Iterable's core platform. Collaborate with teams to integrate AI/ML technologies, evaluate algorithm performance, and develop machine learning pipelines.
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