Senior Machine Learning Research Scientist
Company Name:
Analog Devices
Company Overview:
Analog Devices (NASDAQ: ADI) is a world leader in the design, manufacture, and marketing of a broad portfolio of high performance analog, mixed-signal, and digital signal processing (DSP) integrated circuits (ICs) used in virtually all types of electronic equipment. Since our inception in 1965, we have focused on solving the engineering challenges associated with signal processing in electronic equipment. Used by over 100,000 customers worldwide, our signal processing products play a fundamental role in converting, conditioning, and processing real-world phenomena such as temperature, pressure, sound, light, speed, and motion into electrical signals to be used in a wide array of electronic devices. We focus on key strategic markets where our signal processing technology is often a critical differentiator in our customers' products, namely the industrial, automotive, communications, and consumer markets.
We currently produce a wide range of innovative productsincluding data converters, amplifiers and linear products, radio frequency (RF) ICs, power management products, sensors based on microelectromechanical systems (MEMS) technology and other sensors, and processing products, including DSP and other processorsthat are designed to meet the needs of our broad base of customers.
Description:
Lyric Labs is an internal startup accelerator within Analog Devices, Inc. We build amazing hardware and software products that solve challenging real-world problems. The lab is currently working on hardware accelerated statistical inference, mixed signal semiconductor design, and machine learning algorithms. Our group specializes in algorithmic research to work on problems such as:
What is the GPU of machine learning?
Can we redefine how processors work to make statistical inference more efficient?
How should processing of sensor output be partitioned between special-purpose local hardware and general-purpose cloud resources?
How can we democratize machine learning and make it available to 1000x more people?
Our team is working in areas such as core machine learning, mathematical modeling, and hardware-accelerated probabilistic inference with applications in audio processing, communications infrastructure, vital signs monitoring, and low-power semantic signal processing.
We are looking for senior research scientists to define and execute long-term research projects, develop innovative algorithms, and work with partners across the organization, such as hardware engineers, to incorporate their technology into real-world products that impact millions of people. Our research team stays current on state-of-the-art algorithms, technologies, and theories. The team maintains world-class academic credentials through publications, presentations, external collaborations, and service to the research community. We iterate, we collaborate, and we learn. Come help us define the future of probabilistic computing!
You will be working with a group of motivated individuals and you will be joining them at a great time! Our team is still small enough that we feel like a startup, but we have enough financial backing to really make a difference in our target areas. As part our team, you will have an opportunity to shape our strategy, learn new technologies, and grow with us.
Scope of this role:
This posting is for a senior research scientist and algorithm developer in the areas of machine learning and probabilistic inference. Background in areas such as hardware, software, or systems engineering is a plus, but is neither the primary focus nor sufficient to be considered for the position.
On a more personal note, we encourage a very healthy work-life balance and most of us devote a somewhat significant amount of time to passion projects outside of work. You will tackle daunting problems with talented co-workers who also happen to be down to earth and a lot of fun. We work hard together, we laugh a lot, we perpetually brainstorm, and we are very flexible. We want you to feel like every member of the team is someone you are excited to work with every day!
Qualifications:
MS or PhD in Computer Science, Electrical Engineering, Applied Math, or related area.
Excellent knowledge of machine learning techniques and experience applying these to real problems with real data.
DIY/hacker orientation; skill in and enjoyment of taking things apart and putting them back together again.
Desire to work in a generous and collegial environment.
Expertise in probabilistic modeling and multiple approaches to probabilistic inference.
Expertise in building parallel and distributed architectures for machine learning and/or a deep understanding of processors and processor architectures.
First class expertise in at least one machine learning sub-domain, such as deep learning, distributed learning, social network analysis, semi-supervised learning, multi-task learning, graphical models, structured learning, spectral learning, etc.
Excellent communications skills and a passion for learning and problem solving.
Exceptional research track record, including top-tier peer-reviewed conferences and journals, participation on program committees, editorial boards, and advisory panels.
For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) may have to go through an export licensing review process.
Analog Devices, Inc. is an Equal Opportunity Employer Minorities/Females/Vet/DisabilityEstimated Salary: $20 to $28 per hour based on qualifications.
Analog Devices
Company Overview:
Analog Devices (NASDAQ: ADI) is a world leader in the design, manufacture, and marketing of a broad portfolio of high performance analog, mixed-signal, and digital signal processing (DSP) integrated circuits (ICs) used in virtually all types of electronic equipment. Since our inception in 1965, we have focused on solving the engineering challenges associated with signal processing in electronic equipment. Used by over 100,000 customers worldwide, our signal processing products play a fundamental role in converting, conditioning, and processing real-world phenomena such as temperature, pressure, sound, light, speed, and motion into electrical signals to be used in a wide array of electronic devices. We focus on key strategic markets where our signal processing technology is often a critical differentiator in our customers' products, namely the industrial, automotive, communications, and consumer markets.
We currently produce a wide range of innovative productsincluding data converters, amplifiers and linear products, radio frequency (RF) ICs, power management products, sensors based on microelectromechanical systems (MEMS) technology and other sensors, and processing products, including DSP and other processorsthat are designed to meet the needs of our broad base of customers.
Description:
Lyric Labs is an internal startup accelerator within Analog Devices, Inc. We build amazing hardware and software products that solve challenging real-world problems. The lab is currently working on hardware accelerated statistical inference, mixed signal semiconductor design, and machine learning algorithms. Our group specializes in algorithmic research to work on problems such as:
What is the GPU of machine learning?
Can we redefine how processors work to make statistical inference more efficient?
How should processing of sensor output be partitioned between special-purpose local hardware and general-purpose cloud resources?
How can we democratize machine learning and make it available to 1000x more people?
Our team is working in areas such as core machine learning, mathematical modeling, and hardware-accelerated probabilistic inference with applications in audio processing, communications infrastructure, vital signs monitoring, and low-power semantic signal processing.
We are looking for senior research scientists to define and execute long-term research projects, develop innovative algorithms, and work with partners across the organization, such as hardware engineers, to incorporate their technology into real-world products that impact millions of people. Our research team stays current on state-of-the-art algorithms, technologies, and theories. The team maintains world-class academic credentials through publications, presentations, external collaborations, and service to the research community. We iterate, we collaborate, and we learn. Come help us define the future of probabilistic computing!
You will be working with a group of motivated individuals and you will be joining them at a great time! Our team is still small enough that we feel like a startup, but we have enough financial backing to really make a difference in our target areas. As part our team, you will have an opportunity to shape our strategy, learn new technologies, and grow with us.
Scope of this role:
This posting is for a senior research scientist and algorithm developer in the areas of machine learning and probabilistic inference. Background in areas such as hardware, software, or systems engineering is a plus, but is neither the primary focus nor sufficient to be considered for the position.
On a more personal note, we encourage a very healthy work-life balance and most of us devote a somewhat significant amount of time to passion projects outside of work. You will tackle daunting problems with talented co-workers who also happen to be down to earth and a lot of fun. We work hard together, we laugh a lot, we perpetually brainstorm, and we are very flexible. We want you to feel like every member of the team is someone you are excited to work with every day!
Qualifications:
MS or PhD in Computer Science, Electrical Engineering, Applied Math, or related area.
Excellent knowledge of machine learning techniques and experience applying these to real problems with real data.
DIY/hacker orientation; skill in and enjoyment of taking things apart and putting them back together again.
Desire to work in a generous and collegial environment.
Expertise in probabilistic modeling and multiple approaches to probabilistic inference.
Expertise in building parallel and distributed architectures for machine learning and/or a deep understanding of processors and processor architectures.
First class expertise in at least one machine learning sub-domain, such as deep learning, distributed learning, social network analysis, semi-supervised learning, multi-task learning, graphical models, structured learning, spectral learning, etc.
Excellent communications skills and a passion for learning and problem solving.
Exceptional research track record, including top-tier peer-reviewed conferences and journals, participation on program committees, editorial boards, and advisory panels.
For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) may have to go through an export licensing review process.
Analog Devices, Inc. is an Equal Opportunity Employer Minorities/Females/Vet/DisabilityEstimated Salary: $20 to $28 per hour based on qualifications.
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