Top Senior Machine Learning Engineer Jobs in NYC, NY

Own and improve production-scale ML models and systems for Spotify Home feed and Shortcuts. Build personalized recommendations and LLM-powered experiences, train and fine-tune LLMs, run A/B tests, optimize inference and cost, and improve ML platform, data pipelines, and production infrastructure at scale.

Design, scale, and maintain low-latency, high-throughput ML inference infrastructure and feature stores; implement observability, validation, and automated model deployment; debug relevance systems; partner with product, data engineering, and Trust & Safety to deliver reliable, production-grade ML infrastructure.

The role demands a Senior Software Engineer skilled in backend development and ML, focusing on delivering ML solutions that address business challenges across various domains.

The role involves designing and deploying machine learning systems for content safety at Spotify, collaborating with various stakeholders, and providing technical leadership.

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.

Design and deploy production recommendation and retrieval engines, build data orchestration pipelines for multiple modalities, implement agentic workflow frameworks, and prototype, optimize, and scale models with monitoring, governance, and low-latency SLAs.

Lead design, training, fine-tuning, and deployment of ML and generative models (LLMs, diffusion). Build scalable MLOps pipelines, vectorization and data ingestion, integrate models into microservices for low-latency inference, implement evaluation/alignment/bias-mitigation, optimize models (quantization, distillation), and mentor engineers while influencing the AI product roadmap.

As a Senior Machine Learning Engineer, you will design and maintain ML systems for content recommendations, search, and spam detection, while augmenting user experience and system 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.

Design, build, and deploy high-throughput ML and LLM-powered personalization and agentic systems at consumer scale. Process petabyte-scale data, optimize real-time inference, implement resilient fallback paths, and balance latency, cost, and model quality while collaborating across engineering and product teams.

The Senior Machine Learning Engineer will develop and enhance ML systems for content resolution and work on multimodal understanding involving music, video, and metadata. Responsibilities include leading ML pipeline evolution, experimentation for quality improvements, and mentoring team members.

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.

Design, build, and deploy large-scale ML systems for ad ranking, bid optimization, and recommendations. Build and operate production ML pipelines (feature engineering, distributed training, deployment, retraining, monitoring) that process billions of events and serve low-latency predictions. Optimize training and inference for compute and cost efficiency. Partner with Data Science, Data Engineering, and product teams to ship models, run online experiments, and measure CTR/CVR/ROI impact. Incorporate applied ML research and techniques into advertising and audience modeling.

Design, optimize, and deploy deep learning models for customer behavior prediction. Perform feature engineering, implement research-informed architectures, scale training pipelines, collaborate with client teams, document findings, and uphold engineering best practices.

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 develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

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 build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

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.

The Senior Machine Learning Engineer will build and optimize ML systems for CRM marketing, collaborating with cross-functional teams to impact customer engagement and product functionality.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Lead design and shipping of large-scale optimization algorithms for ad campaigns, balancing multi-objective goals, exploration-exploitation strategies, and long-term impact measurement. Build metrics frameworks, LLM-based agentic automation for diagnostics and recommendations, and provide cross-functional technical leadership from model design to real-time production auctions.

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.

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.