ML Engineer

Job Description: 

Join Intel's Supply Chain Planning IT team to drive digital transformation in demand forecasting and supply planning. We are seeking a highly skilled and motivated Machine Learning (ML) Engineer to join our team, focusing on optimizing our Demand and Supply Planning processes to optimize global supply chain processes and deliver enterprise solutions. The ideal candidate will leverage their ML expertise, domain knowledge in supply chain planning, and experience with specialized planning platforms to drive significant improvements in forecast accuracy, supply optimization, and operational efficiency.Key Responsibilities Design, develop, and deploy end-to-end Machine Learning models (e.g., time series, deep learning, tree-based models) for forecasting demand, optimizing supply, and improving inventory allocation. Integrate ML models with existing planning platforms (Blue Yonder, SAP, etc.) and data infrastructure. Establish MLOps best practices for model deployment, monitoring, retraining, and performance tracking in a production environment. Collaborate with planning and business teams to translate complex business problems into viable ML solutions and measurable outcomes. Work as part of an Agile work team, actively participating in sprint planning, reviews, and retrospectives. Utilize project management tools like Jira or similar applications to manage tasks, track progress, and communicate effectively across teams. Maintain high-quality technical documentation for models, code, and infrastructure.ML Enginner Builds machine learning workflows and infrastructure necessary to productize AI models and sustain them in production. Responsible for preparing data for ML models at scale, building appropriate inference interfaces for ML model consumption, enabling ML Ops for continuous delivery and automation of ML pipelines, and/or building and sustaining AI productization platforms.

Qualifications:

You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Minimum Qualifications:

• The candidate must have a bachelor's degree in Computer Engineering, Computer Science, Information Technology or other Engineering related field and 6+ years of experience -OR- a master's degree in Computer Engineering, Computer Science, Information Technology or other Engineering related field and 4+ years of experience -OR- a PhD in Computer Engineering, Computer Science, Information Technology or other Engineering related field and 2+ years of experience in:

• Demand Forecasting and Demand Planning transformation Sales Forecasting, Statistical forecasting, system-driven disaggregation, Sales and Operations Planning Process transformation experience within a larger program.

• Requirements gathering, systems/business analysis, process mapping, solution acceptance testing and deployment.

• Designing and deploying solutions using enterprise planning software solutions such as SAP IBP, Blue Yonder, JDA DM, i2, Kinaxis, SAP BPC, Anaplan, Demantra, SAP APO or equivalent.

• Product backlog, feature definition, requirements analysis, functional design/specifications, solution delivery, testing, user training, TCM (transition change management).

Required Skills Experience:

• 5+ years of professional experience as an ML Engineer, Data Scientist, or similar role focusing on supply chain or forecasting applications.

• Technical Stack: Expertise in programming languages, primarily Python (including libraries like scikit learn, TensorFlow, PyTorch, Pandas).

• Proficiency in writing complex SQL queries and optimizing data extraction.

• Cloud and Data Warehousing: Experience working with the Snowflake data platform.

• Familiarity with cloud services, specifically Microsoft Azure (e.g., Azure ML, Azure Data Factory, AKS).

• Methodologies: Solid understanding and practical application of Agile development principles and experience using Jira or comparable tools.

Education:

Bachelor's or masters degree in computer science or data science, Industrial Engineering, Operations Research, or a related quantitative field.

Preferred:

• Blue Yonder or equivalent applications (SAP, Kinaxis, O9), Planning experience.

• Semiconductor/high-tech industry background.

• Familiarity with cloud platforms (Azure, Snowflake) and data pipelines for analytics.