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Job Requirements of Senior Research Engineer, Machine Learning and DSE Algorithms, Software, and Systems:
-
Employment Type:
Full-Time
-
Location:
San Jose, CA (Onsite)
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Senior Research Engineer, Machine Learning and DSE Algorithms, Software, and Systems
Bayone Solutions Inc
San Jose, CA (Onsite)
Full-Time
Description:
Senior Research Engineer, Machine Learning and DSE Algorithms, Software, and Systems
Responsibilities
Collaborate with the machine learning team in exploring and advancing AI/ML/SL algorithms and systems
Support new technology and research initiatives and implement leading-edge PoC with best practices focus on Large Foundation Models, AI for Science, DSE and Inverse Design, using open-source technologies.
Collaborate with in-house and academic researchers focused on applications of reinforcement learning and other machine learning technologies in various fields, including computing, micro-architecture, chip, device and materials design.
Collaborate with researchers in various areas of design space exploration (DSE) and inverse design with practical applications demonstrated in the design pipeline.
Communicate complex ideas and testing results effectively, both orally and in writing
Lead and contribute to papers and patents as deliverable
Qualifications
PhD in Electrical Engineering and/or Computer Science or related fields with solid background in research, software and system engineering
Experience with multi-processing libraries and python-based machine learning is a strong plus
Experience with Linux and Docker environments is a plus
Advanced understanding of technical troubleshooting approaches, tools and techniques, and the ability to anticipate, recognize, and resolve technical problems arising in research involving open-source technologies
Several years of innovative and algorithmic software development with hands-on experiences in a software engineering role, including collaboration with other engineers and researchers
Deep knowledge of machine learning, statistical learning and reinforcement learning.
Ability to work productively with various statistical learning, optimization and auto-differentiation platforms (e.g., PyTorch, Tensorflow, etc.)
Proficient and productive in at least two programming languages e.g., Python, C/C++ with an ability to learn new languages, systems and platforms, ability to work productively with open-sourced research software
Strong sense of product ownership and business impact
Eagerness to learn new technologies
Excellent oral and written communication skills
Senior Research Engineer, Machine Learning and DSE Algorithms, Software, and Systems
Responsibilities
Collaborate with the machine learning team in exploring and advancing AI/ML/SL algorithms and systems
Support new technology and research initiatives and implement leading-edge PoC with best practices focus on Large Foundation Models, AI for Science, DSE and Inverse Design, using open-source technologies.
Collaborate with in-house and academic researchers focused on applications of reinforcement learning and other machine learning technologies in various fields, including computing, micro-architecture, chip, device and materials design.
Collaborate with researchers in various areas of design space exploration (DSE) and inverse design with practical applications demonstrated in the design pipeline.
Communicate complex ideas and testing results effectively, both orally and in writing
Lead and contribute to papers and patents as deliverable
Qualifications
PhD in Electrical Engineering and/or Computer Science or related fields with solid background in research, software and system engineering
Experience with multi-processing libraries and python-based machine learning is a strong plus
Experience with Linux and Docker environments is a plus
Advanced understanding of technical troubleshooting approaches, tools and techniques, and the ability to anticipate, recognize, and resolve technical problems arising in research involving open-source technologies
Several years of innovative and algorithmic software development with hands-on experiences in a software engineering role, including collaboration with other engineers and researchers
Deep knowledge of machine learning, statistical learning and reinforcement learning.
Ability to work productively with various statistical learning, optimization and auto-differentiation platforms (e.g., PyTorch, Tensorflow, etc.)
Proficient and productive in at least two programming languages e.g., Python, C/C++ with an ability to learn new languages, systems and platforms, ability to work productively with open-sourced research software
Strong sense of product ownership and business impact
Eagerness to learn new technologies
Excellent oral and written communication skills
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