Description

Explore big data from manufacturing and supply chains and identify unique business insights to drive critical decision making Develop machine learning (ML) and operations research (OR) algorithms and tools, such as regression, classification, deep learning and optimization models for various manufacturing applications. Analyze large amounts of data to identify anomalies (pattern detection) and identify predictive signals. Deploy efficient and scalable ML solution to production system. Collaborate with Apples cross-functional teams to apply and deploymachine learning to industrial problems.Key Qualifications: 5+ years hands-on experience in building analytics and machine learning algorithms to solve real-world problems. 2+ years experience in productionalizing ML system (MLOps). 2+ years experience in cloud-based ML dev and deployment (AWS). Strong programing skills with proficiency in Python and Github. Experienced user of machine learning libraries such as scikit-learn,scipy, and Tensorflow/PyTorch. Ability to explain and present machine learning concepts and resultsto a broad technical audience and executives.Bonus Points: 2+ years experience in SQL and data modeling. Knowledge of full-stack ML development such as Flask (backend),Bokeh, Holoviews or Dash (front-end). Experience with Operations Research (OR) and nonlinearconstrained or black-box optimization. Experience in machine data (sensors, downtime, machine states, etc)for IoT & predictive maintenance applications. Experience applying deep learning frameworks, such as PyTorch/Torch, TensorFlow, Keras to real world applications. Experience in data analytics, machine learning and/or computervision for manufacturing problems is a bonus.

Role and Responsibilities

• Explore big data from manufacturing and supply chains and identify unique business insights to drive critical decision making Develop machine learning (ML) and operations research (OR) algorithms and tools, such as regression, classification, deep learning and optimization models for various manufacturing applications. Analyze large amounts of data to identify anomalies (pattern detection) and identify predictive signals. Deploy efficient and scalable ML solution to production system. Collaborate with Apples cross-functional teams to apply and deploymachine learning to industrial problems.Key Qualifications: 5+ years hands-on experience in building analytics and machine learning algorithms to solve real-world problems. 2+ years experience in productionalizing ML system (MLOps). 2+ years experience in cloud-based ML dev and deployment (AWS). Strong programing skills with proficiency in Python and Github. Experienced user of machine learning libraries such as scikit-learn,scipy, and Tensorflow/PyTorch. Ability to explain and present machine learning concepts and resultsto a broad technical audience and executives.Bonus Points: 2+ years experience in SQL and data modeling. Knowledge of full-stack ML development such as Flask (backend),Bokeh, Holoviews or Dash (front-end). Experience with Operations Research (OR) and nonlinearconstrained or black-box optimization. Experience in machine data (sensors, downtime, machine states, etc)for IoT & predictive maintenance applications. Experience applying deep learning frameworks, such as PyTorch/Torch, TensorFlow, Keras to real world applications. Experience in data analytics, machine learning and/or computervision for manufacturing problems is a bonus.