Top Senior Machine Learning Jobs in NYC, NY

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

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.

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

Lead ML Engineer for Finance Tech to design, build, deploy, and maintain AI/ML systems (including LLMs and RAG). Partner cross-functionally to create production data pipelines, model evaluation, governance, observability, and responsible AI practices while contributing technical vision and scaling AI infrastructure.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.

Lead development and production deployment of advanced ML/AI pricing models across Home, Renters, Car, and Pet lines. Own end-to-end projects, align stakeholders, mentor junior data scientists, set technical standards, and drive adoption of advanced data science practices within Insurance.

Lead end-to-end development, validation, and deployment of large-scale predictive models. Drive rigorous data-driven research, translate business goals into analytical frameworks, and communicate findings to executives. Mentor data scientists and partner with engineering and stakeholders to productionize ML solutions and define long-term analytics strategy.

Lead architecture and implementation of ML-driven features (including generative AI/LLMs and optimization) across cloud and mobile. Build production model deployment, CI/CD and experimentation infrastructure, define technical strategy from ambiguous product requirements, and own Agile delivery and technical risk communication while collaborating with Product, Engineering, and Data Science.

Design, build, and deploy machine learning models to detect fraud, prevent losses, and monitor risk. Work with Product, Engineering, and Operations to turn large-scale data into production-ready pipelines and model-serving solutions, monitor performance, and continuously improve model accuracy and business impact.

As a Senior AI Engineer, you'll develop and deploy innovative AI solutions for the fashion industry, collaborate with cross-functional teams, and refine machine learning models to enhance product offerings.

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.

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.

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 Senior Research Engineer will develop and deliver scalable ML solutions, collaborate with teams, and apply innovative technologies in AI to impact professionals in legal and accounting fields.

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, development, validation, and cloud deployment of advanced time-series forecasting and explainable ML models for finance and risk. Build AI agentic systems, run simulation and uncertainty quantification, produce model risk documentation, and collaborate with business, finance, and risk stakeholders to translate needs into dashboards, reports, and compliant models.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.

Design, build, deploy, and maintain production-scale ML models and pipelines. Collaborate with product and data science teams to architect ML systems, implement model training and monitoring, optimize performance and reliability, and apply Responsible/Explainable AI practices using cloud and distributed computing technologies.

Lead end-to-end improvements to Hinge's recommendation system, partnering with data science, ML, engineering, design, and research to personalize ranking, run experiments, protect fairness and trust, define roadmaps, and drive measurable user and business outcomes.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

As Lead ML Engineer, you will architect and build a conversational AI interface, optimize models for deployment, and collaborate with a multidisciplinary team.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.