Top Machine Learning Engineer Jobs in NYC, NY

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.

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.

Design, develop, and deploy machine learning models to address various business needs. Collaborate with cross-functional teams to integrate ML solutions into advertising technology platform. Monitor and optimize deployed models. Manage ML infrastructure and tools. Stay updated on industry trends and technologies.

Architect and lead the design of scalable MLOps pipelines, oversee repo management, implement robust monitoring frameworks, drive platform improvements, raise engineering standards, establish data lineage processes, and develop data versioning and model management systems.

Lead the design, research, modeling, engineering, and evaluation of ML models and systems at CNN. Collaborate with cross-functional teams on ML projects from ideation to completion. Mentor and influence engineers across organizations. Drive innovation and advocate for customer-centric practices.

Build, optimize, and deploy machine learning models to support identity resolution and ads attribution. Collaborate with cross-functional teams to meet company objectives and stay up-to-date with the latest technology in machine learning.

Machine Learning Engineer specializing in NLP to join the Responsible AI team at Grammarly. Develop and implement new ML solutions to improve safety and fairness of Grammarly products. Work in small cross-functional teams to leverage ML advances and human-centered design.

As a Lead Machine Learning Engineer at Capital One, you will be responsible for designing, building, and delivering ML models to solve real-world business problems. You will work closely with cross-functional teams to develop and implement machine learning applications at scale. Responsibilities include model training, infrastructure decision-making, and ensuring high availability and performance of ML applications.

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 Senior Machine Learning Engineer at Capital One, you will be responsible for designing, building, and delivering ML models to solve real-world business problems. You will work collaboratively with product and data science teams, inform ML infrastructure decisions, write and test application code, and automate deployment processes.

As a Senior Machine Learning Engineer at Capital One, you will be responsible for designing, building, and delivering ML models to solve real-world business problems. You will collaborate with cross-functional teams to develop and implement ML applications at scale, leveraging cloud-based architectures and continuous integration best practices. The role requires at least 4 years of programming experience with Python, Scala, or Java, as well as expertise in designing data-intensive solutions and working with ML frameworks like scikit-learn and PyTorch.

Lead Machine Learning Engineer role at Capital One focusing on productionizing machine learning applications and systems at scale. Responsibilities include designing, developing, and implementing machine learning applications using various technologies, supporting and developing workflows in Kubernetes-based platforms, scaling out big-data workloads, and collaborating with data scientists and software reliability experts.

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.

Senior Machine Learning Engineer at Rokt, responsible for designing and building proprietary machine learning models for various business challenges. Collaborate with teams to create engaging Ad content and model features using the latest Generative AI techniques. Mentor team members and stay updated on emerging technologies.

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.