Top Machine Learning Engineer Jobs in NYC, NY

Principal Machine Learning Engineer responsible for architecting ML solutions, developing tools and services to streamline ML development and deployment processes, collaborating with data practitioners, defining best practices, and working on complex projects in an Agile environment.

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.

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 Machine Learning Engineer II to build and enhance models for precision mental health care, develop AI platforms, and contribute to innovative data products. Collaborate with data science teams and improve recommender systems and data products using GenerativeAI.

Grubhub is looking for a Data Scientist or Machine Learning Engineer to work in the Search and Discovery team. Responsibilities include creating metrics, proposing algorithmic approaches, designing A/B tests, mentoring junior data scientists, and driving technology best practices. The focus is on personalized recommendations and classification using various machine learning techniques like deep neural networks and transfer learning.

Build, orchestrate, and monitor model pipelines, scale machine learning algorithms, implement ML Ops, write production-ready code, collaborate with client teams, and contribute to researching and evaluating new technologies.

Looking for a technical leader to shape the Machine Learning agenda for Dropbox's new initiatives. Develop high-impact ML solutions using various techniques and work on machine learning products for millions of users.

Play a major part in building AI and Machine Learning solutions to transform user experience and workflow efficiency of enterprise services. Develop and implement machine learning models, facilitate ML data preparation, and support ML strategy for Enterprise Data Platform.

Create machine learning models for ranking, recommendations, search, content understanding, or image generation. Evaluate technical tradeoffs, perform code reviews, and ensure code quality. Collaborate with internal and external partners to solve problems and build scalable products.

Create machine learning models to drive value for users, advertisers, and the company. Evaluate technical tradeoffs, perform code reviews, and ensure high code quality. Build lasting and scalable products iteratively without compromising quality.

Design, implement, and scale critical machine learning components and services to support Snap's most strategic initiatives. Develop next-generation training framework for large-scale model training. Provide technical direction influencing the entire company. Advocate for best practices in availability, scalability, and operational excellence.

Lead Machine Learning Engineer at Disney Entertainment & ESPN Technology responsible for developing and implementing machine learning algorithms for personalization and recommendation systems. Collaborate with cross-functional teams to meet strategic product personalization goals and optimize operational processes. Lead algorithm research, development, implementation, and maintenance for content recommendations.

As a Lead Machine Learning Engineer at Personio, you will provide technical leadership, design and deploy scalable ML algorithms, mentor junior engineers, and shape the Machine Learning landscape within the organization. This hybrid role is based in New York City.

Senior Machine Learning Engineer at Capital One responsible for designing, building, and delivering ML models to solve real-world business problems. Will work with cross-functional teams to develop and maintain ML applications using tools like Python, PySpark, and TensorFlow.

As a Senior Lead Machine Learning Engineer at Capital One, you will be responsible for designing, building, and delivering ML models to solve real-world business problems, leading teams in developing ML solutions, and ensuring high availability and performance of machine learning applications.

As a Senior Lead Machine Learning Engineer at Capital One, you will be responsible for designing, building, and delivering ML models and components to solve real-world business problems. You will work on ML architectural design, model code development and review, and ensuring high availability and performance of ML applications. Additionally, you will collaborate with cross-functional teams, retrain and monitor models in production, and leverage cloud-based architectures for optimized ML models.

Lead Machine Learning Engineer at Capital One responsible for designing, building, and delivering ML models and components to solve real-world business problems. Focus on ML architectural design, model development, and application code to ensure high performance and availability. Collaborate in Agile teams to enhance big data and ML applications using cloud-based architectures and continuous integration best practices. Required skills include Python, Scala, Java, and experience in building, scaling, and optimizing ML systems.