Keystone AI
CoreAI Senior Scientist – Applied Deep Learning
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. 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 to drive the development of our foundation forecasting capabilities—Keystone’s flagship product for cutting‑edge time series forecasting and intelligent inventory management. In this role, you will work closely with scientists and ML engineers, shaping the design and deployment of deep learning models for forecasting, inventory control, and data‑driven insights. The position is based in NYC, NY, with open relocation to Bellevue, WA.
What You’ll Do
Champion deep learning innovations in time series forecasting, supply chain optimization, and inventory control.
Guide cross‑functional teams of data scientists and ML engineers through model development, best practices, and project delivery.
Design and refine deep learning architectures that accurately forecast demand, manage inventories, and extract actionable insights from complex data sets.
Collaborate with product managers, economists, research scientists, and software engineers to create scalable end‑to‑end AI solutions that address real business needs.
Drive continuous innovation by exploring novel techniques and ensuring solutions remain cutting‑edge.
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 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 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.
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Position Overview Keystone’s Core AI team is seeking a Senior Scientist to drive the development of our foundation forecasting capabilities—Keystone’s flagship product for cutting‑edge time series forecasting and intelligent inventory management. In this role, you will work closely with scientists and ML engineers, shaping the design and deployment of deep learning models for forecasting, inventory control, and data‑driven insights. The position is based in NYC, NY, with open relocation to Bellevue, WA.
What You’ll Do
Champion deep learning innovations in time series forecasting, supply chain optimization, and inventory control.
Guide cross‑functional teams of data scientists and ML engineers through model development, best practices, and project delivery.
Design and refine deep learning architectures that accurately forecast demand, manage inventories, and extract actionable insights from complex data sets.
Collaborate with product managers, economists, research scientists, and software engineers to create scalable end‑to‑end AI solutions that address real business needs.
Drive continuous innovation by exploring novel techniques and ensuring solutions remain cutting‑edge.
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 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 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.
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