Grainger
Manager, Applied Machine Learning
We are looking for a highly motivated Manager, Applied Machine Learning Science to lead a team of world-class machine learning scientists and engineers. You will drive initiatives that design, develop, and deliver scalable ML and AI solutions that directly shape business decisions, improve operational effectiveness, and unlock new value across the company. Combining both a strong technical depth with leadership and vision guide a team that builds high-impact ML products and infrastructure, while fostering a culture of experimentation, learning, and continuous improvement. You will identify new opportunities where ML, optimization, and intelligent automation can transform the business, and work cross-functionally to turn those ideas into production-ready solutions. You will: Own the end-to-end relationship with business partners understanding complex problems, identifying opportunities, and translating them into scalable ML solutions Lead, mentor, and grow a team of machine learning scientists and engineers; set direction, define priorities, and foster technical excellence and collaboration Drive the design, development, and delivery of scalable machine learning and deep learning models that improve the effectiveness and efficiency of core business operations Oversee the creation of robust ML pipelines from ideation and prototyping to automated, production-grade systems Apply advanced methods such as classification, regression, NLP, deep learning, LLMs, time series forecasting, and Bayesian inference to build impactful solutions Encourage and support the development of interactive analytical tools (e.g. React, Streamlit) to visualize model outputs and enhance collaboration with business users Explore and apply optimization, simulation, and decision-science techniques to augment predictive models with prescriptive intelligence Implement rigorous model validation, monitoring, and continuous improvement practices (e.g., drift detection, retraining, hyperparameter tuning) Promote automation and standardization across ML workflows to improve scalability and reproducibility Stay current with emerging ML/AI technologies and research, evaluating their potential to drive innovation and competitive advantage Communicate analytical insights, model performance, and business impact clearly to executives and stakeholders You have: MS degree or PhD in Mathematics, Data Science, Applied Analytics, Operations Research, Computer Science, Applied Science, or Engineering 5+ year's of hands-on experience delivering production-grade machine learning solutions at scale Previous experience leading, mentoring, and developing a high-performing ML/AI team Advanced proficiency in Python and SQL for data manipulation and model development Hands-on experience with machine learning frameworks and deployment tools (e.g., scikit-learn, PyTorch, TensorFlow, MLflow, REST APIs) Familiarity with containerization, CI/CD, and version control (Kubernetes, Docker, Git) Experience building interactive, model-driven applications using React, Streamlit, or similar frameworks Proven ability to apply deep learning and transformer-based modeling methods in production environments Strong analytical and problem-solving mindset; able to translate complex business challenges into structured, data-driven solutions Solid understanding of MLOps practices, model registry, drift monitoring, and hyperparameter optimization Experience with databases (Teradata, Snowflake, S3) and data processing at scale Strong understanding of modern ML architectures, including embedding models, multimodal systems, or generative AI (LLMs, diffusion models) where applicable. Proven ability to lead cross-functional collaborations and influence technical and business stakeholders Excellent communication skills, with the ability to convey technical concepts to both technical and business audiences We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, protected veteran status or any other protected characteristic under federal, state, or local law. We are proud to be an equal opportunity workplace. We are committed to fostering an inclusive, accessible work environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one's employment.
We are looking for a highly motivated Manager, Applied Machine Learning Science to lead a team of world-class machine learning scientists and engineers. You will drive initiatives that design, develop, and deliver scalable ML and AI solutions that directly shape business decisions, improve operational effectiveness, and unlock new value across the company. Combining both a strong technical depth with leadership and vision guide a team that builds high-impact ML products and infrastructure, while fostering a culture of experimentation, learning, and continuous improvement. You will identify new opportunities where ML, optimization, and intelligent automation can transform the business, and work cross-functionally to turn those ideas into production-ready solutions. You will: Own the end-to-end relationship with business partners understanding complex problems, identifying opportunities, and translating them into scalable ML solutions Lead, mentor, and grow a team of machine learning scientists and engineers; set direction, define priorities, and foster technical excellence and collaboration Drive the design, development, and delivery of scalable machine learning and deep learning models that improve the effectiveness and efficiency of core business operations Oversee the creation of robust ML pipelines from ideation and prototyping to automated, production-grade systems Apply advanced methods such as classification, regression, NLP, deep learning, LLMs, time series forecasting, and Bayesian inference to build impactful solutions Encourage and support the development of interactive analytical tools (e.g. React, Streamlit) to visualize model outputs and enhance collaboration with business users Explore and apply optimization, simulation, and decision-science techniques to augment predictive models with prescriptive intelligence Implement rigorous model validation, monitoring, and continuous improvement practices (e.g., drift detection, retraining, hyperparameter tuning) Promote automation and standardization across ML workflows to improve scalability and reproducibility Stay current with emerging ML/AI technologies and research, evaluating their potential to drive innovation and competitive advantage Communicate analytical insights, model performance, and business impact clearly to executives and stakeholders You have: MS degree or PhD in Mathematics, Data Science, Applied Analytics, Operations Research, Computer Science, Applied Science, or Engineering 5+ year's of hands-on experience delivering production-grade machine learning solutions at scale Previous experience leading, mentoring, and developing a high-performing ML/AI team Advanced proficiency in Python and SQL for data manipulation and model development Hands-on experience with machine learning frameworks and deployment tools (e.g., scikit-learn, PyTorch, TensorFlow, MLflow, REST APIs) Familiarity with containerization, CI/CD, and version control (Kubernetes, Docker, Git) Experience building interactive, model-driven applications using React, Streamlit, or similar frameworks Proven ability to apply deep learning and transformer-based modeling methods in production environments Strong analytical and problem-solving mindset; able to translate complex business challenges into structured, data-driven solutions Solid understanding of MLOps practices, model registry, drift monitoring, and hyperparameter optimization Experience with databases (Teradata, Snowflake, S3) and data processing at scale Strong understanding of modern ML architectures, including embedding models, multimodal systems, or generative AI (LLMs, diffusion models) where applicable. Proven ability to lead cross-functional collaborations and influence technical and business stakeholders Excellent communication skills, with the ability to convey technical concepts to both technical and business audiences We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex (including pregnancy), national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, protected veteran status or any other protected characteristic under federal, state, or local law. We are proud to be an equal opportunity workplace. We are committed to fostering an inclusive, accessible work environment that includes both providing reasonable accommodations to individuals with disabilities during the application and hiring process as well as throughout the course of one's employment.