Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses.
Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include automated pricing and demand forecasting for hundreds of millions of products, predicting ad click probabilities, ranking product search results, matching products from multiple sources, classifying products into large taxonomies, information extraction, sentiment analysis for product reviews, natural language understanding, question answering, conversational systems, etc.
We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers.
We encourage thought leadership and blue ocean thinking in ML.
· Use machine learning and analytical techniques to create scalable solutions for business problems
· Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes
· Design, develop, evaluate and deploy, innovative and highly scalable ML models
· Work closely with software engineering teams to drive real-time model implementations
· Work closely with business partners to identify problems and propose machine learning solutions
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance
· Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production
· Leading projects and mentoring other scientists, engineers in the use of ML techniques
· MS or PhD in Computer Science/Machine learning/Operational research/Statistics or in allied areas
· 7+ years of hands-on experience in applied Machine Learning and Big data
· Strong grasp of machine learning, data mining and data analytics techniques
· Strong problem-solving ability
· Understanding of computer science algorithms and data structures
· Strong expertise in two or more of the Machine Learning domains like NLP, Computer Vision, Reinforcement Learning, etc.
· Knowledge of SQL or related languages for data processing
· Strong knowledge of scientific programming in languages like Python
· PHD in any of the following disciplines - Computer Science, Machine Learning, Data Mining, Statistics, Operational Research
· Superior verbal and written communication skills
· Ability to convey rigorous mathematical concepts and considerations to non-experts
· Experience of working with large scale data on distributed system using languages like Spark, Scala, etc.
· Publications in top-tier conferences and journals