Machine Learning Engineer

Operations Advanced Analytics team is looking for creative and motivated hands on individual contributors who thrive in dynamic environment and enjoy working with multi-functional teams As a member of our team, you will work on applied machine-learning algorithms to seek problems that focus on topics such as classification, regression, clustering, optimizations and other related algorithms to impact and optimize Apple s supply chain and manufacturing processes As a part of this role, you would work with the team to build end to end machine learning systems and modules, and deploy the models to our factories Youll be collaborating with Software Engineers, Machine Learning Engineers, Operations, and Hardware Engineering teams across the company 4+ years experience formulating complex business problems into actionable data solutions. 4+ years hands-on experience in building large scale ML systems to solve real world problems. Master s or PhD degree in Computer Science, Math, Statistics, Physics, Engineering or related level of experience required. Strong communicator and experience with communicating complex ML outcomes to non-technical engineers. Intuitive understanding of machine learning algorithms, supervised and unsupervised modeling techniques and their performance characteristics. Experience working with large scale and real world datasets. Experience with machine learning tools and libraries such as TensorFlow, Scikit-learn, R, Spark, PyTorch. Experience with ML in manufacturing and operations spaces are pluses. In particular, working with extensive and messy manufacturing data set, as well as deploying production ready model to the factory. Strong programming skills with 4+ years experience in Python for ML. Experience with full-stack ML development (e.g., Flask, JavaScript) and productionalizing ML system using AWS. Preferred Qualifications Experience with Operations Research (OR) and linear & nonlinear constrained optimization. Work experience in machine data (sensors, downtime, machine states, etc) for IoT & predictive maintenance applications. Experience with manufacturing and supply chain ML use cases such as test optimization, cost reduction, and quality improvement. Experience with ML for business decisions.