Top Machine Learning Jobs in NYC
Experiment with state-of-the-art algorithms to improve knowledge retrieval and search efficiency, develop NLP and Gen AI models for customer support, collaborate with cross-functional teams, monitor and evaluate model performance, and prepare reports on model trends.
Act as a security domain expert in partnership with Compliance, Legal, and Engineering. Collaborate across roles and functions, prioritize security efforts, and automate governance and compliance functions using scripting languages like Python or data tools. Interpret and communicate security constraints to stakeholders and monitor changes in security regulations and standards.
Develop and implement machine learning models for fraud detection, analyze datasets for fraudulent activities, collaborate with teams to mitigate fraud risks, monitor model performance, stay updated on machine learning trends, and prepare reports for stakeholders.
Develop advanced algorithms and execute statistical techniques on large data sets. Evaluate emerging datasets and technologies, contribute to thought leadership, and have strong analytical and quantitative skills.
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.
Lead strategic planning and execution for scalable machine learning infrastructure and products at JP Morgan Asset Management. Collaborate with data science and business teams to deliver end-to-end machine learning applications and data pipelines. Manage and support a global team of ML and MLOps engineers. Operate in a multi-cloud environment with a focus on AWS and Azure technologies.
Apply sophisticated machine learning methods to tasks such as NLP, speech analytics, time series predictions, and recommendation systems. Collaborate with various teams to deploy solutions into production and drive firm-wide initiatives by developing large-scale frameworks for the application of machine learning models.
Develop scalable tools using machine learning and deep learning models for finance applications at JPMorgan Chase. Lead project development by collaborating with various business lines to deploy production-level machine learning applications. Required qualifications include a PhD in a quantitative discipline, minimum 3 years of experience, and strong knowledge of machine learning theory and techniques.
Featured Jobs
Lead a team of applied scientists to drive strategic direction through collaboration with Applied Science, Engineering, and Product leaders at Capital One. Partner with cross-functional teams to deliver AI-powered products, build AI foundation models, engage in high-impact applied research, and translate technical work into tangible business goals.
The Senior Applied AI Scientist will be responsible for building, evaluating, and shipping products that use AI models. They will develop Gusto Assistant, improve LLMs, collaborate with AI/ML infrastructure teams, and research novel AI techniques.
GoodRx is looking for an experienced Senior Machine Learning Engineer to enable and accelerate our machine learning efforts. The ideal candidate should possess practical, hands-on data and analytics technical expertise and strong understanding of various machine learning models. Responsibilities include developing and implementing analytical capabilities, building machine learning models and pipelines, improving infrastructure, and mentoring junior engineers.
Join our AI team to incorporate ML technologies into our product and explore the boundaries of what's possible. Prototype and experiment with AI model quality improvements and collaborate with cross-functional teams to deliver product features.
.png)
Seeking a Senior Machine Learning Engineer to develop NLP algorithms, train large language models, preprocess data, drive entity resolution solutions, collaborate with teams, and contribute to research initiatives. Must have 5 years of ML experience with NLP focus, proficiency in Python and relevant ML libraries, and a Bachelor's degree in computer science or related field.
Design and develop scalable and high-quality AI/ML models and infrastructure for Celonis products. Collaborate with cross-functional teams to meet the business needs of customers and drive innovation in execution management systems.
As a software engineer (machine learning), you are responsible for designing and developing product features and customer solutions, along with the underlying infrastructure, that are based on AI/ML approaches.
Develop and implement machine learning models for fraud detection, analyze large datasets, collaborate with cross-functional teams, monitor model performance, and stay up-to-date with the latest machine learning and fraud detection techniques.
Top Companies Hiring Data + Analytics Roles
See All
All Filters
No Results
No Results
