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MLSys 2021: Bridging the divide between machine learning and systems

MLSys 2021: Bridging the divide between machine learning and systems

Machine learning
MLSys 2021: Bridging the divide between machine learning and systems
Amazon distinguished scientist and conference general chair Alex Smola on what makes MLSys unique — both thematically and culturally.
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Alex Smola, Amazon vice president and distinguished scientist
The Conference on Machine Learning and Systems ( MLSys ), which starts next week, is only four years old, but Amazon scientists already have a rich history of involvement with it. Amazon Scholar  Michael I. Jordan  is on the steering committee; vice president and distinguished scientist  Inderjit Dhillon  is on the board and was general chair last year; and vice president and distinguished scientist  Alex Smola , who is also on the steering committee, is this year’s general chair.
As the deep-learning revolution spread, MLSys was founded to bridge two communities that had much to offer each other but that were often working independently: machine learning researchers and system developers.
Conference registration still open
Read more  about Amazon’s involvement with MLSys, including paper presentations and workshop participation. Registration for the conference is  still open , with the very low fees of $25 for students and $100 for academics and professionals.
“If you look at the big machine learning conferences, they mostly focus on, ‘Okay, here's a cool algorithm, and here are the amazing things that it can do. And by the way, it now recognizes cats even better than before,’” Smola says. “They're conferences where people mostly show an increase in capability. At the same time, there are systems conferences, and they mostly care about file systems, databases, high availability, fault tolerance, and all of that. 
“Now, why do you need something in-between? Well, because quite often in machine learning, approximate is good enough. You don't necessarily need such good guarantees from your systems. If you lower the requirement, you can do things cheaper, faster, or more scalably.”
Sys for ML, ML for sys
At the same time, as deep learning’s popularity grew, it was natural to ask whether it could help allocate resources in computer systems.
“This is, ultimately, what a lot of systems papers do,” Smola says. “They are along the lines of, Should I start a machine? Should I end one? How many devices should I schedule for a job? When do I decide that a machine has failed? How much redundancy do I need? So you can ask yourself, Well, given that these are a lot of resource decisions, can I use machine learning to predict what an optimal or at least a better strategy will be to handle those resource decisions?”
Should I start a machine? Should I end one? How many devices should I schedule for a job? ... Can I use machine learning to predict what an optimal or at least a better strategy will be?
Alex Smola
Papers accepted to MLSys, Smola explains, feature research in both directions — machine learning for systems and systems for machine learning. As an example, he pulls up the  program listing  for the conference session on Communication and Storage, on Tuesday, April 6.
“This is very much a systems session,” Smola says. “But even there, it covers both directions. For instance, the paper ‘In-network aggregation for shared machine learning clusters’ is about how you can do operations cheaply to facilitate more machine learning. But another paper is about how to use machine learning to make those storage systems themselves better.”
Cultural fusion
MLSys doesn’t just represent a merger of research programs, Smola says; it also represents a merger of cultures — which can make for some lively discussion.
“In the systems community, essentially, unless you actually have a working system, they won't take you seriously,” Smola says. “That makes the conference a little bit interesting, because you have two different cultures. You have the machine learning culture, where it's more like, ‘Hey, here is an impressionist painting of what could be. Next paper, please.’ And then the systems community, which is a lot more rigorous in terms of, ‘Well, here's something that actually works, and hey, we've demonstrated it. And by the way, maybe there's a product that's actually shipping now with it.’ And that makes the conference interesting, because those two cultures usually don't mix quite that much. And this maybe gives the systems papers a slightly more theoretical bent and the machine learning papers a slightly more empirical one.”
At this year’s MLSys, one of the additions that Smola oversaw is the introduction of a daylong Chips and Compilers Symposium, which brings the conversation about system design for machine learning down to the metal — the chip level. The symposium was organized by  Mu Li , a senior principal scientist with Amazon Web Services.
“There are events like  Hot Chips  and  Cool Chips  where NVIDIA, Intel, AMD, ARM, and others show up and demonstrate the latest silicon,” Smola says. “But the silicon is only half the equation. So we figured this would be a good place to bring these two communities much more closely together. This is a community-building exercise.”
Like all computer science conferences in the past year, MLSys has moved online. The advantage of that, Smola says, is that it has drastically reduced the price of registration — $25 for students and $100 for academics and professionals.
“It's super affordable for anybody,” Smola says.
Research areas
Larry Hardesty is the editor of the Amazon Science blog. Previously, he was a senior editor at MIT Technology Review and the computer science writer at the MIT News Office.
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Data Scientist, AWS Training & Certification
US, Virtual
The Amazon Web Services (AWS) Training and Certification (T&C) organization educates customers, partners, and AWS Employees globally on AWS products, solutions, and best practices. We are seeking a talented and experienced Data Scientist to perform data analytics, create forecasting processes to influence business strategies, and analyze customer trends to make recommendations to improve their training & certification journey.As part of the AWS Training and Certification Business Intelligence and Data Analytics team you will analyze data to provide insights using statistical methods and processes. We are looking for someone who is comfortable getting into data and will uncover patterns and performance that can be used to influence business strategies. The right candidate will be passionate about working with large datasets and should be someone who loves to bring data together to answer complex business questions that deepen our understanding of our business drivers. As a Data Scientist within AWS, you will have the exciting opportunity to help analyze and deliver data driven insights that will broaden AWS’s penetration in the cloud computing market.The ideal candidate will have a background in analyzing and deriving insights from data by using SQL (e.g. Redshift), analytics (e.g. R, Python), statistical processes (e.g. machine learning, forecasting, and predictive analytics), and business intelligence tools (e.g. Tableau). A successful candidate should have the technical proficiency to develop code to produce processes that analyze our data and the business proficiency to summarize their findings and report to the AWS Training and Certification leadership team. This role will work closely with Business Intelligence Engineers, Business Analyst, Economists, Program Managers, and AWS T&C Leadership.Responsibilities:· Serve as a key member of the AWS Training & Certification Business Intelligence and Data Analytics team by turning data into actionable insights and providing support for strategic initiatives.· · Conduct analysis of existing metrics and create new metrics that will be shared with the Global Operations Team and executive stakeholders.· · Recommend, develop, and manage machine learning/statistical processes and tools.· · Conducts data analyses with the appropriate statistical approach (regressions, linear and non-linear correlation, entropy, t-test, F-test, etc.)· · Identify needed data for projects and understand underlying structure (distribution, variable independence, outliers, etc.), and develop process to help improve data quality· · Influence the decisions of senior business leaders through effective verbal and written communication and logical reasoning.· · Able to discuss and present data science processes to business leaders and provide support to help with understanding of processes to non-tech individuals.· · Manage numerous requests concurrently and strategically, prioritizing when necessary.· · Drive and support projects that help build AWS into the most customer-centric technology platformThis role can be performed near any US AWS office in the following cities: Arlington, Atlanta, Austin, Ballston, Boston, Chicago, Cupertino, Dallas, Denver, Detroit, East Palo Alto, Herndon, Houston, Irvine, Minneapolis, New York City, Pittsburgh, Portland, San Diego, San Francisco, Seattle, Washington D.C., Tempe, Sunnyvale, or Santa Monica.The pay range for this position in Colorado is $119,300 - $160,000/yr; however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site.
Senior Applied Scientist
PL, Gdansk
Our team undertakes research together with multiple organizations to advance the state-of-the-art in speech technologies. We not only work on giving Alexa, the ground-breaking service that powers Echo, her voice, but we also develop cutting-edge technologies with Amazon Studios, the provider of original content for Prime Video. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history.We are looking for a passionate, talented, and inventive Senior Applied Scientist with a background in Machine Learning, to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Text-to-Speech (TTS) in order to provide the best-possible experience for our customers.As an Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech synthesis.Position Responsibilities:· Participate and lead the design, development, evaluation, deployment and updating of data-driven models for text-to-speech applications.· Participate in research activities including the application and evaluation of text-to-speech techniques for novel applications.· Research and implement novel ML and statistical approaches to add value to the business.· Mentor junior engineers and scientists.
Senior Machine Learning Scientist
GB, Cambridge
Our team undertakes research together with multiple organizations to advance the state-of-the-art in speech technologies. We not only work on giving Alexa, the ground-breaking service that powers Echo, her voice, but we also develop cutting-edge technologies with Amazon Studios, the provider of original content for Prime Video. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history.We are looking for a passionate, talented, and inventive Senior Machine Learning Scientist to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Text-to-Speech (TTS) in order to provide the best-possible experience for our customers.As a ML Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech synthesis.Position Responsibilities:· Participate and lead the design, development, evaluation, deployment and updating of data-driven models for text-to-speech applications.· Participate in research activities including the application and evaluation of text-to-speech techniques for novel applications.· Research and implement novel ML and statistical approaches to add value to the business.· Mentor junior engineers and scientists.
Machine Learning Scientist, Speech and Language
GB, Cambridge
Our team undertakes research together with multiple organizations to advance the state-of-the-art in speech technologies. We not only work on giving Alexa, the ground-breaking service that powers Echo, her voice, but we also develop cutting-edge technologies with Amazon Studios, the provider of original content for Prime Video. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history.We are looking for a passionate, talented, and inventive Machine Learning Scientist to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Text-to-Speech (TTS) in order to provide the best-possible experience for our customers.As a ML Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to advance the state of the art in speech synthesis.Position Responsibilities:· Participate in the design, development, evaluation, deployment and updating of data-driven models for text-to-speech applications.· Participate in research activities including the application and evaluation of text-to-speech techniques for novel applications.· Research and implement novel ML and statistical approaches to add value to the business.· Mentor junior engineers and scientists.
Deep Learning Scientist, Speech and Vision
GB, Cambridge
Our team undertakes research together with multiple organizations to advance the state-of-the-art in speech technologies. We not only work on giving Alexa, the ground-breaking service that powers Echo, her voice, but we also develop cutting-edge technologies with Amazon Studios, the provider of original content for Prime Video. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history.We are looking for a passionate, talented, and inventive Deep Learning Scientist to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Text-to-Speech (TTS) in order to provide the best-possible experience for our customers.As a Deep Learning Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to advance the state of the art in speech synthesis.Position Responsibilities:· Participate in the design, development, evaluation, deployment and updating of data-driven models for text-to-speech applications.· Participate in research activities including the application and evaluation of text-to-speech techniques for novel applications.· Research and implement novel ML and statistical approaches to add value to the business.· Mentor junior engineers and scientists.

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