CoreAI Senior Scientist – Applied Deep Learning

Company Overview

Keystone.ai is a global technology and services firm specializing in enterprise AI, economics advisory and technology strategy. Keystone’s Deep Enterprise™ AI platform—built by AI/ML industry pioneers—helps large enterprises optimize business decisions at scale. By combining advanced technology, strategic consulting, and applied econometrics, Keystone delivers innovative solutions to organizations across the technology, business, legal, and government sectors. Founded in 2003, Keystone operates globally with offices in New York, San Francisco, Boston, Seattle, London, and Dubai.

Position Overview

Keystone’s Core AI team is seeking a Senior Scientist who will help drive the development of our foundation forecasting capabilities—Keystone’s flagship product for cutting-edge time series forecasting and intelligent inventory management. Our Core AI team builds advanced AI applications deployed for clients across diverse industries, helping them transform mission-critical processes, reduce waste, and modernize operations through deep learning–powered automation.

In this role, you will work closely with other scientists and ML engineers, shaping the design and deployment of deep learning models for forecasting, inventory control, and data-driven insights. You will leverage your extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch) to produce innovative and industry-leading solutions that optimize supply chain and operational workflows.

If you are passionate about pushing the boundaries of AI, mentoring high-performing teams, and collaborating closely with business and technical stakeholders to deliver end-to-end solutions, we invite you to apply. This is the future of supply chain forecasting and optimization, and we are poised to deliver it. This position is based in NYC, NY. We would also be open to someone sitting in Bellevue, WA.

What You’ll Do

• Provide Thought and Invention: Contribute to the strategy and vision for Keystone’s Core AI team by championing deep learning innovations in time series forecasting, supply chain optimization, and inventory control.
• Cross-functional Collaboration: Contribute as a member of a multidisciplinary team of data scientists and ML engineers, guiding them in model development, best practices, and impactful project delivery.
• Develop Advanced Models: Design and refine deep learning architectures that accurately forecast demand, manage inventories, and extract actionable insights from complex data sets across industries.
• Collaborate Cross-Functionally: Work closely with product managers, data scientists, economists, research scientists, software engineers, and ML engineers to create scalable, end-to-end AI solutions that address real business needs.
• Drive Innovation: Contribute to the evolution of Keystone’s foundation forecasting capabilities by exploring novel techniques, ensuring our solutions remain on the cutting edge.
• Champion Operational Excellence: Ensure models are robust, efficient, and production-ready, accelerating time-to-market for AI-driven applications.

Basic Qualifications

• PhD in Machine Learning, Statistics, Industrial Engineering, Operations Research, Optimization, or an equivalent quantitative field.
• 3-5 years of overall experience in machine learning and statistical modeling, including exposure to time series forecasting and large-scale data analysis.
• Hands-on expertise in deep learning frameworks (e.g., PyTorch, TensorFlow) with a proven track record of successfully deploying deep neural architectures in production.
• Demonstrated ability to lead and mentor teams of scientists, ML engineers, or related technical roles.
• Excellent communication skills, with the ability to convey complex technical concepts to a variety of stakeholders and executives.

Preferred Qualifications

• Experience developing deep learning solutions in supply chain contexts, including forecasting, demand planning, and inventory optimization.
• Familiarity with building innovative solutions in emerging areas such as Generative AI, advanced statistical analysis, and quantitative optimization.
• Background in building enterprise-scale AI systems that operate in fast-paced, cross-industry environments.
• Desire to work in a self-directed, entrepreneurial culture where innovation and fast iteration are the norm.