Top Hybrid Machine Learning Jobs in New York City, NY
As a Distinguished Machine Learning Engineer at Capital One, you'll lead the productionization of machine learning applications, guiding architectural decisions, developing models, and optimizing data pipelines. You will collaborate across teams to deliver ML solutions while mentoring engineers and applying innovative technologies in financial services.
As a Senior Data Scientist in the Emerging ML team, you will conduct research, build machine learning models, analyze customer behavior, and collaborate with engineering and product teams to improve customer experiences and business outcomes. You'll work across all phases of the data science lifecycle and utilize various data to create impactful solutions.
The Senior Machine Learning Engineer will be responsible for productionizing machine learning applications, ensuring high performance and availability while collaborating with cross-functional teams. Key tasks include designing and deploying ML models, constructing data pipelines, and adhering to best practices in responsible AI.
As a Machine Learning Scientist focused on Speech AI and NLP, you will research and produce advanced machine learning models and applications, collaborate across the firm to develop impactful software solutions, and design scalable data processing pipelines for optimizing business results. You will prioritize innovative learning and knowledge sharing.
The Machine Learning Summer Associate will research and develop advanced machine learning models, focusing on areas like natural language processing and recommendation systems, while collaborating with various teams to deploy solutions. The role includes independent research, experimentation with new methods, and participation in a knowledge-sharing community.
As a Sr. Machine Learning Engineer, you will leverage large-scale computation and machine learning to enhance customer products. You will oversee dataset analysis, lead model development, manage ML Ops, and communicate complex issues effectively while fostering a collaborative environment for improved user experiences.
The Applied AI Scientist will develop advanced algorithms and execute statistical techniques on large datasets to identify trends. Responsibilities include evaluating emerging datasets, owning the development of assets for scaling capabilities, and contributing to the firm's thought leadership through research and publication.
As a Machine Learning Engineer at ZS, you'll build and monitor model pipelines, scale algorithms for massive data sets, implement ML Ops, and produce high-quality code. You will collaborate with global teams, participate in scrum calls, and contribute to researching new technologies.
Featured Jobs
The Senior Machine Learning Engineer will create end-to-end AI and machine learning solutions, collaborating with stakeholders to define project requirements, gather data, and deploy models into production. Responsibilities include analyzing data for insights, managing projects from start to finish, and staying updated on industry trends to drive innovation.
Snap Inc. is looking for a Machine Learning Engineer with 5+ years of experience to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, building scalable products, and iterating quickly without compromising quality.
Create machine learning models to drive value for users, advertisers, and the company. Evaluate technical tradeoffs, perform code reviews, and ensure code quality. Build scalable products iteratively without compromising quality.
The Principal Machine Learning Engineer will design and implement machine learning components, build a large-scale training framework, optimize model performance with GPUs, and develop an AutoML platform. They will collaborate across teams to meet product requirements and ensure high availability and scalability.
.png)
The Senior Machine Learning Engineer will develop and optimize NLP algorithms, train large language models, collaborate with cross-functional teams, and mentor junior engineers, all while advancing the company's technology stack and delivering new features rapidly.
The Machine Learning Infra Engineer will bridge the gap between data science and production systems by optimizing models for runtime performance, designing scalable MLOps pipelines, and implementing monitoring frameworks. They will work closely with data scientists to improve workflows and ensure reliability across the system, while also developing data versioning and deployment strategies.
Top hybrid Companies in New York City, NY Hiring Data + Analytics Roles
See All
.png)
All Filters
No Results
No Results
