Top Machine Learning Jobs in NYC, NY

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Join Spotify as a Machine Learning Intern to experiment with AI tools, prototype ideas, and collaborate in a supportive environment.

As a Machine Learning Engineer, you'll design and implement scalable ML systems, develop data pipelines, support model experimentation, and collaborate across teams to deliver impactful ML solutions.

As a Senior AI Engineer, you'll develop and deploy innovative AI solutions for the fashion industry, collaborate with cross-functional teams, and refine machine learning models to enhance product offerings.

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

As an Open-Source Machine Learning Engineer, you'll improve the ML ecosystem using existing libraries and engage with the community, enhancing accessibility to AI tools.

As a Lead Machine Learning Engineer, you'll design and implement machine learning applications, collaborate with teams, and ensure model performance at scale.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

As a Senior Machine Learning Engineer on the Perception Team, you will define technology direction, architect solutions for autonomous vehicles, collaborate with team members, and mentor junior engineers, contributing to high-stakes projects in autonomous driving.

The ML Engineer will work on RL frameworks, develop synthetic data engines, and maintain performance evaluations for a closed-loop drug discovery platform.

The role involves building a recommendation engine, designing ML systems, making data-driven decisions, and collaborating with leadership to enhance user experiences.

The Senior Machine Learning Engineer will develop and optimize algorithms for Zocdoc's Sponsored Results product, improving healthcare experiences. Responsibilities include designing scalable ML infrastructure, mentoring peers, and collaborating across teams.

This role involves developing ML models for Hinge, collaborating with teams, deploying models, and optimizing systems for performance and cost.

The role involves designing and implementing reinforcement learning pipelines for AI systems, integrating organizational data, and collaborating with product teams to enhance AI functionalities.

The Senior Machine Learning Engineer will develop foundational models for recommendations, mentor engineers, and collaborate on improving user experiences with machine learning.

The role involves designing ML models, research, improving ML capabilities, mentoring engineers, and managing data at scale utilizing cloud platforms.

The Senior Machine Learning Engineer leads technology projects, mentors engineers, and collaborates on cloud-based solutions, primarily using languages such as Python and Java.

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

Research Engineer will conduct Machine Learning research to enhance localization and global entertainment, focusing on ASR, Speaker Diarization, and Audio Understanding.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

Lead the development of production-grade ML systems, aligning technical roadmaps with company priorities, mentoring ML engineers, and ensuring ethical use of ML/AI.