Top Machine Learning Engineer Jobs in NYC, NY

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 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.

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 building and scaling machine learning systems for content understanding, improving quality, and collaborating with cross-functional teams to enhance user experience on Spotify.

The Machine Learning Engineer will build tools for interpretable AI, optimize infrastructure, and integrate workflows into products, ensuring reliability and performance.

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

The role involves building and scaling machine learning systems for content moderation, designing evaluation frameworks, and developing multimodal models for policy enforcement, while mentoring other engineers.

Design and build interactive ML features, collaborate with cross-functional teams, and prototype new solutions for enhanced user experiences in audio streaming.

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.

As a Machine Learning Engineer, you will design, build, and improve ML models for Spotify's subscription services, collaborating with cross-functional teams to enhance user experience and increase subscriber retention.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

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 and build core ML systems for Workday's AI agents, manage the full lifecycle from data strategy to deployment, and collaborate across teams.

The role involves deploying ML solutions for business problems, working with stakeholders to gather requirements, architecting AI systems on Google Cloud, and monitoring industry trends.

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

The Machine Learning Engineer will design, develop, and implement advanced recommendation systems, collaborating with cross-functional teams to enhance personalization for a global audience.

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.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

Lead the advancement of embedding-based retrieval systems, focusing on multimodal models, model performance, and extensibility for various use cases.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

Senior AI/ML Engineer responsible for designing, building, and deploying AI/ML systems, mentoring teams, and leading cross-functional collaborations to drive AI solutions.

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.