Top Machine Learning Engineer Jobs in NYC, NY

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 Machine Learning Engineer at Verneek, you'll develop AI/NLP models, tackle complex AI research problems, and innovate within an early-stage deep-tech startup environment.

The Senior Staff Machine Learning Engineer will lead and execute machine learning strategies focused on generative recommenders and personalization systems to enhance user experience on Spotify.

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 building machine learning systems for Radar's products, focusing on core ML infrastructure, anomaly detection, geolocation, and collaboration with customers.

As a Sr Lead Machine Learning Engineer, you'll design, develop, and implement machine learning applications, collaborating with cross-functional teams and ensuring high performance and governance of ML systems.

As a Senior Machine Learning Engineer, you'll design and manage ML infrastructure, work with Data Science to implement models, and oversee system health and reliability.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

The role involves developing an ML research platform, managing data pipelines, and building tools for simulation lifecycle and performance monitoring in a collaborative environment.

Develop and improve machine learning models and systems for clinical outcomes. Lead ML initiatives, mentor teams, and establish best practices in AI. Collaborate across engineering, product, and design for data-driven solutions.

The role involves designing and improving AI/ML platforms and operational infrastructure, collaborating with engineers and product managers, and mentoring teams on MLOps best practices.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

As a Senior Principal Machine Learning Engineer, you'll lead technical projects, mentor teams, and implement ML systems, focusing on AI in AEC solutions.

The Staff ML Engineer will define and build ML capabilities, focusing on production systems, strategy, and infrastructure in a cybersecurity context.

As a Founding ML Engineer, you will build advanced document processing systems, train models, design LLM techniques, and monitor model performance while collaborating directly with leadership.

Drive the strategic vision for machine learning initiatives, lead development of models, oversee data analysis, and mentor teams.

The role involves designing and maintaining ML infrastructure, solving complex technical problems, and collaborating with engineers and data scientists.

The intern will assist in training and evaluating machine learning models, using AI tools for development, and providing feedback on features, while validating model performance and usability.

As a Machine Learning Engineer, lead the architecture and development of AI capabilities, specifically for LLMs in the Agentic AI Platform. Collaborate closely with customers and design evaluation methodologies for machine learning systems while staying abreast of NLP research.

As an ML Engineer, you will develop and deploy machine learning models, collaborate on research, and mentor team members in materials science applications.

The Machine Learning Engineer will design, build, and ship production-grade AI systems, collaborating with teams to optimize workflows and evaluate AI results.

As an AI/ML Engineer, you'll design, build, and ship large scale NLP and LLM systems for classification, ranking, and content generation while collaborating with cross-functional teams.

Design and implement AI-driven features for claims synthesis, leveraging LLMs and statistical techniques, while ensuring system performance and accuracy.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

The ML Engineer will build custom models and data systems for the AI platform, focusing on enhancing ML capabilities in the insurance domain and managing the full ML lifecycle including data pipelines and evaluation frameworks.