Top Remote Machine Learning Engineer Jobs in NYC

The Applied Machine Learning Engineer will develop AI-driven solutions, focusing on backend systems, AI integration, model deployment, and MLOps best practices, while collaborating with cross-functional teams.

Lead the architecture and development of AI and ML features, design evaluation frameworks, and mentor team members to enhance ML-driven product experiences.

As a Senior Applied Machine Learning Engineer, you will develop machine learning solutions, manage project lifecycles, and integrate data into production systems.

The Machine Learning Engineer will enhance search retrieval, train ranking models, build query understanding systems, and ensure robust pipelines for Reddit's AI-driven products.

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

As a Senior Staff Machine Learning Engineer, you'll lead projects on ML models for search and recommendations, impacting over 150M users. Responsibilities include improving ML systems, collaborating with cross-functional teams, and developing infrastructure for model deployment.

The Staff Machine Learning Engineer at Niche will lead ML initiatives, build and deploy models, measure results, mentor staff, and drive business growth through data-driven solutions.

Seeking a machine learning engineer to build solutions for personalization, automated experimentation, predictive modeling, and content generation, impacting customer interactions.

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

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

As a Machine Learning Engineer, you will develop online prediction systems and offline recommendation engines to optimize e-commerce profitability by leveraging machine learning models and data-driven insights.

Lead development of a large-scale machine learning platform, optimizing model training, data processing, and collaborating on MLOps, while ensuring scalability and performance.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

The Senior Machine Learning Engineer will develop AI workflows, collaborate with teams on models and pipelines, conduct research, mentor junior members, and innovate solutions for healthcare.

We're looking for an AI/ML Engineer to enhance our edge MLOps solutions, improve ML workflows, and support team development with strong technical expertise in Python and ML frameworks.

The Senior Machine Learning Engineer will evaluate and apply advanced ML models, integrate with company infrastructure, and support data pipeline orchestration while focusing on autonomous vehicle technology.

As a Senior Consultant II, you will integrate AI technologies into business applications, build scalable microservices, and deploy AI models in production environments.

Develop and optimize large-scale ML models and training pipelines for automating PCB layouts, collaborating on data pipeline design and novel architectures.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

Develop ML models and pipelines for autonomous tractor initiative, improving system safety and performance in production environments.

Drive and implement machine learning applications, optimize practices, formulate hypotheses, and communicate requirements to enhance advertising strategies and systems.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

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

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

As a Machine Learning Engineer, you will fine-tune models, shape data pipelines, evaluate AI behavior, and collaborate on product features in a high-autonomy environment.