ASRC Federal
Job Description
ASRC Federal, InuTeq proudly supports NASA's High Performance Computing Services program with our site in Mountain View, CA at the Ames Research Center. Make a DIFFERENCE on a program that supports 4 On-site Supercomputers totaling 18,000 nodes and 17+ combined petaflops. Our program provides High Performance Computing services throughout the HPC lifecycle for computational requirements, architecture, acquisition, and operations to federal government customers. Our employees embrace innovation and are committed to a culture of continuous, standards-driven, process improvement, and assimilation of industry best practices.
We have an immediate position for a Senior HPC Applications Manager to join our HPC team in Mountain View.US Citizenship is required.
Summary
HPC Application Services and Tools
HPC Cloud Computing
Data Science Applications supporting HPC Users
HPC Visualization
The Application Services and Tools technical subtask focuses on enhancing the performance and productivity of NASA’s advanced modeling, simulation, and data analysis applications. The goal is to solve complex application problems, decrease time-to-solution, and increase the achievable scale and fidelity of the applications. The result is an increase of user and facility productivity, which in turn enhances NASA’s science and engineering. This subtask requires high performance application expertise in many of the following areas: state-of-the-art parallel architectures; parallel programming paradigms in shared memory, distributed memory, and emerging systems with heterogeneous processors and multiple memory subsystems; scientific computing programming languages, such as C / C++ and Fortran; parallel computing models, such as Message Passing Interface (MPI) and OpenMP, as well as offloading models for accelerators, such as general purpose graphic processing units (GPGPUs); hybrid computational approaches using MPI with threads or other models; deep understanding of parallel software development and profiling tools; and related technologies and tools in support of data analysis, such as machine learning. The subtask also provides support for performance monitoring and benchmarking of various parallel systems available on site and evaluating emerging architectures and technologies available in various locations, including commercial cloud.
The Cloud sub-task seeks opportunities and capabilities beyond traditional high-performance computing (HPC), such as cloud computing, cloud application services, and machine learning, to meet the ever-increasing demand of various scientific and engineering requirements. The team continually evaluates its options for cost-effective delivery of HPC and other relevant services. This requirement focuses explicitly on cloud computing as a complementary approach for the traditional HPC.
The purpose of the Data Science subtask is to evaluate and explore the use of Machine Learning (ML) technologies to identify methods that can be applied to science projects to enable scientific breakthroughs, to speed up the acquisition of science results, and/or to improve their fidelity.
The Visualization and Data Analysis subtask develops and employs advanced visualization and data analysis in both interactive and batch environments to enable users to derive increased value from their computations and observational data streams. The overarching goal of this technical area is to provide enhanced routes to discovery by way of scientifically rich visualizations, incisive data analysis techniques, interactive exploratory environments for large and complex data, and efficient data management strategies. The general approach will be application driven, using an evolving portfolio of customer science and engineering problems to develop and deploy new and existing visualization and data analysis techniques that maximally exploit the high-performance computational resources at the NAS.
Duties and Responsibilities
Manage day-to-day performance of approximately 15 direct reports, providing technical leadership and oversight
Work with NASA customer counterparts to achieve contract objectives and requirements
Varying levels of direct technical contributions in support of HPC application and optimization activities
Plan and achieve project objectives; technically guide projects through completion and ensure all project objectives are met within target time frames.
Partner with development and operations teams to develop automation solutions
Location
NASA / AMES, MOFFETT FIELD-CA
Requirements
Advanced degree in Computer Science or related HPC dependent field
A minimum of 10 years of meaningful experience developing system software in heterogeneous, multi-platform HPC environments
Solid understanding of the software development process, including requirements, use cases, design, coding, documentation, and testing of scalable, distributed applications in a Linux environment
Demonstrated experience managing projects using various industry best practices and tools
Strong ability to analyze, debug and maintain the integrity of an existing code base
Experience working with HPC applications and proficiency in at least C, C++, or Fortran
Superior scripting skills and excellent attention to detail; proficiency in at least Python, Perl, or Bash
Strong ability to interact with customers to understand needs, elicit requirements, and get feedback on prototype solutions
Excellent communication and people skills; excellent time management and organizational skills
Track record of delivering commercial quality software on schedule with excellent quality through multiple release cycles
Proficiency at technical writing
Preferred Skills
Computer Science or related HPC dependent field
Project Management Professional Certification
Background in rendering techniques, ray tracing and graphics standards, OpenGL
Proficiency with analysis and problem-solving skills for debugging and optimization of applications.
Proficiency with OpenMP and Message Passing Interface (MPI) programming.
Proficiency with Lustre and InfiniBand
Experience with Machine Learning technologies such as TensorFlow, PyTorch
Experience with cloud technologies (AWS, Azure, GCP), OpenStack or Kubernetes is a plus
GPU experience, CUDA programming a plus
EEO Statement ASRC Federal and its Subsidiaries are Equal Opportunity / Affiant Action employers. All qualified applicants will receive consideration for employment without regard to race, gender, color, age, sexual orientation, gender identification, national origin, religion, marital status, ancestry, citizenship, disability, protected veteran status, or any other factor prohibited by applicable law.
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ASRC Federal, InuTeq proudly supports NASA's High Performance Computing Services program with our site in Mountain View, CA at the Ames Research Center. Make a DIFFERENCE on a program that supports 4 On-site Supercomputers totaling 18,000 nodes and 17+ combined petaflops. Our program provides High Performance Computing services throughout the HPC lifecycle for computational requirements, architecture, acquisition, and operations to federal government customers. Our employees embrace innovation and are committed to a culture of continuous, standards-driven, process improvement, and assimilation of industry best practices.
We have an immediate position for a Senior HPC Applications Manager to join our HPC team in Mountain View.US Citizenship is required.
Summary
HPC Application Services and Tools
HPC Cloud Computing
Data Science Applications supporting HPC Users
HPC Visualization
The Application Services and Tools technical subtask focuses on enhancing the performance and productivity of NASA’s advanced modeling, simulation, and data analysis applications. The goal is to solve complex application problems, decrease time-to-solution, and increase the achievable scale and fidelity of the applications. The result is an increase of user and facility productivity, which in turn enhances NASA’s science and engineering. This subtask requires high performance application expertise in many of the following areas: state-of-the-art parallel architectures; parallel programming paradigms in shared memory, distributed memory, and emerging systems with heterogeneous processors and multiple memory subsystems; scientific computing programming languages, such as C / C++ and Fortran; parallel computing models, such as Message Passing Interface (MPI) and OpenMP, as well as offloading models for accelerators, such as general purpose graphic processing units (GPGPUs); hybrid computational approaches using MPI with threads or other models; deep understanding of parallel software development and profiling tools; and related technologies and tools in support of data analysis, such as machine learning. The subtask also provides support for performance monitoring and benchmarking of various parallel systems available on site and evaluating emerging architectures and technologies available in various locations, including commercial cloud.
The Cloud sub-task seeks opportunities and capabilities beyond traditional high-performance computing (HPC), such as cloud computing, cloud application services, and machine learning, to meet the ever-increasing demand of various scientific and engineering requirements. The team continually evaluates its options for cost-effective delivery of HPC and other relevant services. This requirement focuses explicitly on cloud computing as a complementary approach for the traditional HPC.
The purpose of the Data Science subtask is to evaluate and explore the use of Machine Learning (ML) technologies to identify methods that can be applied to science projects to enable scientific breakthroughs, to speed up the acquisition of science results, and/or to improve their fidelity.
The Visualization and Data Analysis subtask develops and employs advanced visualization and data analysis in both interactive and batch environments to enable users to derive increased value from their computations and observational data streams. The overarching goal of this technical area is to provide enhanced routes to discovery by way of scientifically rich visualizations, incisive data analysis techniques, interactive exploratory environments for large and complex data, and efficient data management strategies. The general approach will be application driven, using an evolving portfolio of customer science and engineering problems to develop and deploy new and existing visualization and data analysis techniques that maximally exploit the high-performance computational resources at the NAS.
Duties and Responsibilities
Manage day-to-day performance of approximately 15 direct reports, providing technical leadership and oversight
Work with NASA customer counterparts to achieve contract objectives and requirements
Varying levels of direct technical contributions in support of HPC application and optimization activities
Plan and achieve project objectives; technically guide projects through completion and ensure all project objectives are met within target time frames.
Partner with development and operations teams to develop automation solutions
Location
NASA / AMES, MOFFETT FIELD-CA
Requirements
Advanced degree in Computer Science or related HPC dependent field
A minimum of 10 years of meaningful experience developing system software in heterogeneous, multi-platform HPC environments
Solid understanding of the software development process, including requirements, use cases, design, coding, documentation, and testing of scalable, distributed applications in a Linux environment
Demonstrated experience managing projects using various industry best practices and tools
Strong ability to analyze, debug and maintain the integrity of an existing code base
Experience working with HPC applications and proficiency in at least C, C++, or Fortran
Superior scripting skills and excellent attention to detail; proficiency in at least Python, Perl, or Bash
Strong ability to interact with customers to understand needs, elicit requirements, and get feedback on prototype solutions
Excellent communication and people skills; excellent time management and organizational skills
Track record of delivering commercial quality software on schedule with excellent quality through multiple release cycles
Proficiency at technical writing
Preferred Skills
Computer Science or related HPC dependent field
Project Management Professional Certification
Background in rendering techniques, ray tracing and graphics standards, OpenGL
Proficiency with analysis and problem-solving skills for debugging and optimization of applications.
Proficiency with OpenMP and Message Passing Interface (MPI) programming.
Proficiency with Lustre and InfiniBand
Experience with Machine Learning technologies such as TensorFlow, PyTorch
Experience with cloud technologies (AWS, Azure, GCP), OpenStack or Kubernetes is a plus
GPU experience, CUDA programming a plus
EEO Statement ASRC Federal and its Subsidiaries are Equal Opportunity / Affiant Action employers. All qualified applicants will receive consideration for employment without regard to race, gender, color, age, sexual orientation, gender identification, national origin, religion, marital status, ancestry, citizenship, disability, protected veteran status, or any other factor prohibited by applicable law.
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