Top Machine Learning Engineer Jobs in NYC, NY

Lead the development of Computer Vision and Machine Learning projects at Dandy, focusing on 3D geometric problems and automation in dental manufacturing.

As a Machine Learning Engineer at Doppel, you will design, train, and deploy ML models for detecting malicious content, ensuring scalability and real-time performance while collaborating with teams and stakeholders.

Machine Learning Engineer needed to enhance ML platform, build infrastructure, and utilize ML frameworks to solve problems in a financial context.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

Design, implement, and scale AI/ML systems and data pipelines for healthcare applications. Own model inference, deployment, monitoring, and reliability; collaborate with cross-functional teams to deliver production ML solutions using cloud and distributed computing.

Lead technical projects for the Workers AI team focused on deploying AI inference, building innovative features, and enhancing developer experience.

As a Staff Machine Learning Engineer at Angi, you'll lead model development, deploy MLOps solutions, collaborate across teams, foster innovation, and mentor juniors to enhance machine learning capabilities.

The role involves building and deploying machine learning solutions, collaborating with stakeholders, and ensuring production-ready systems, with responsibilities across the ML lifecycle.

As a Machine Learning Engineer, you will develop deep generative models, create efficient data pipelines, and evaluate complex biological models in a biotech startup.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

This role involves architecting, building, and deploying AI systems, integrating Generative AI with traditional ML, and developing scalable solutions.

The AI/ML Engineer will develop AI/ML solutions, drive business impact, and collaborate across teams to enhance profitability through advanced analytics.

The Senior AI/ML Engineer designs and implements AI/ML solutions to enhance profitability, while collaborating across teams and communicating insights to business leaders.

Design and scale ML platform infrastructure for large 3D datasets: build training pipelines, deploy generative models, optimize ML lifecycle, ensure cloud-native reliability and observability, and collaborate across engineering.

Lead the architecture and management of AI/ML infrastructure using Kubernetes and Terraform, optimizing hybrid environments for performance and scalability.

The ML Engineer will design, build, and deploy scalable machine learning models while optimizing algorithms, collaborating cross-functionally, and maintaining infrastructure.

Develop and implement machine learning models, optimize algorithms, analyze data trends, and collaborate with cross-functional teams to enhance the platform.

Lead end-to-end design and delivery of Stripe Assistant's ML and agent architecture. Improve answer quality, safety, and execution for high-trust actions using LLMs, RAG, fine-tuning, and agent orchestration. Set SLOs, build evaluation and benchmarking pipelines, optimize latency/cost/reliability, and mentor engineers while collaborating cross-functionally to ship secure, observable, and scalable AI-driven features.

Design, train, deploy, and optimize ML models and pipelines for large-scale, safety-critical systems. Build data ingestion and MLOps infrastructure, validate model reliability, co-author technical reports, and collaborate with engineers and customers to integrate new data sources. Some customer travel required.

As an Applied Machine Learning Engineer, you'll design and optimize LLM models and pipelines, improve permitting workflows, and manage the ML lifecycle.

Develop and maintain ML pipelines for entity classification; collaborate with data scientists; implement monitoring frameworks and improve data workflows.

Seeking a Machine Learning Engineer to apply AI technologies in high frequency trading, focusing on automation and collaboration with AI research.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

The role involves deploying and scaling machine learning models, optimizing systems for ML applications, and collaborating with various teams to support data science functionalities at Squarespace.