Top Senior Machine Learning Engineer Jobs in NYC, NY

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.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead development and productionization of large-scale ranking and personalization ML systems. Build data pipelines, features, and models (batch and real-time), collaborate cross-functionally, run experiments, and improve infrastructure for search, recommendation, and marketplace optimization.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

The Senior Machine Learning Engineer will design, develop, and deploy production ML models, owning the entire ML lifecycle and collaborating with various teams to enhance product experiences and decision-making systems.

Build, operate, and improve production ML systems and platform components (feature store, model registry, CI/CD). Ensure reliability, observability, SLOs, on-call support, drift monitoring, and cost/latency optimization. Partner with ML, data, and product teams to automate model deployment, implement data quality checks and statistical validation, and define MLOps standards and KPIs.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Design, build, and operate production-grade ML systems for personalization, search, and recommendations. Own end-to-end pipelines from data ingestion and modeling to deployment, monitoring, and iteration, ensuring scalable, reliable, and observable services.

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

The Senior ML Engineer will develop and deploy full-stack AI solutions, manage LLM integration, and collaborate closely with defense clients to enhance real-world applications in secure environments.

The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.

As a Senior MLOps Engineer, you will manage production ML systems, define lifecycle strategies, optimize ML pipelines, and collaborate with cross-functional teams to enhance ML operations.

The Senior Machine Learning Engineer will develop, deploy, and optimize large language models on healthcare data, collaborate with teams, and ensure compliance.

The role involves designing and implementing large-scale ML solutions for personalized music experiences, collaborating with cross-functional teams to enhance user interactions and fulfill music recommendations.

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.

The Senior Machine Learning Engineer leads technical direction for ML systems focused on personalization and ranking, overseeing architecture and implementation while mentoring team members.

Design, build, and own production ML and LLM-driven features (RAG, prompt engineering, fine-tuning, semantic search). Write maintainable code, create design docs, troubleshoot issues, collaborate with product/design, and participate in Agile development. Work with Python/Java/JavaScript, ML frameworks, and cloud/container technologies.

Design, build, and operate production-grade GenAI and RAG platforms with strong guardrails, observability, evaluation frameworks, CI/CD, cost/performance monitoring, safety mechanisms, and incident management. Own end-to-end lifecycle for models, prompts, and datasets, partner with product and governance, and mentor engineers to deliver reliable, compliant, and cost-efficient AI systems.

The role involves leading technical initiatives in machine learning infrastructure, developing data pipelines, and collaborating across teams to enhance personalized news content delivery.

Lead the development of machine learning algorithms for personalization and recommendations in Disney's streaming products while collaborating with product and engineering teams.

Design and build core systems for data processing and AI pipelines, ensuring reliability and scalability for enterprise clients while mentoring junior engineers.

Design, train, and deploy scalable ML models (generative, classification, regression). Define feature roadmaps, collaborate with engineering to implement code and APIs, adapt ML methods for distributed/GPU environments, and create evaluation/annotation programs for fine-tuning and performance measurement.