Top AI & Machine Learning Jobs in New York City, NY

Own and build Confido's ML platform: design and operate end-to-end ML pipelines, infrastructure-as-code and CI/CD, optimize training/inference and agent workloads for latency/cost/throughput, integrate model data flows with data engineering, and ensure reliability, observability, security, and production model quality with online evals and human-in-the-loop review.

Lead Confido’s data science function for Revenue Growth Management, developing pricing, promotion, forecasting, causal inference, and optimization models. Translate predictions into actionable recommendations under budget, margin, and retailer constraints. Partner with AI/ML engineers on productionization, evaluation, backtesting, and monitoring. Hire and mentor a team of data scientists while setting technical direction with company leadership.

Build and deploy data science models for demand and sales forecasting, promotion effectiveness, pricing, and retail analytics. Analyze messy datasets from sell-through, inventory, deductions, trade promotions, and supply-chain signals. Develop statistical quality checks, evaluate model performance, quantify uncertainty, and collaborate with AI/ML engineers to ship production-grade insights within the product.

Build and deploy data science models for CPG brands, focusing on demand and sales forecasting, promotion effectiveness, pricing, elasticity, and cannibalization. Analyze messy retail, inventory, trade promotion, and supply-chain data; develop statistical validation and evaluation methods; and communicate model insights and uncertainty to technical and non-technical stakeholders. Collaborate with AI/ML engineers to move analyses into production.

As a Senior AI/ML Engineer, you will manage the AI/ML lifecycle, develop predictive models, conduct anomaly detection, and integrate AI capabilities into the Confido platform.

Design, build, and productionize core AI systems for document understanding, forecasting, and agentic workflows. Handle messy data ingestion, evaluation, monitoring, anomaly detection, entity reconciliation, and backtesting to deliver reliable, product-focused ML solutions.