Argus Array Data Production Engineer
Share
Job Location:
Chapel Hill, NC - USA
Monthly Salary:
$ 51000 - 100000
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Position Summary
The Argus Array will be the largest optical telescope array ever assembled with a collecting area comparable to the largest monolithic telescopes in the world. The Array will push our observations of the universe into a new regime scanning the sky 100000x faster than current nightly-cadence sky surveys. Argus will capture a continuous multi-color 55-gigapixel movie of the night sky shared with the entire astronomical community in real-time through public transient alerts images and light curves with millions of epochs for hundreds of millions of stars. Joining our local team of astronomers telescope-instrumentalists and engineers the Argus Array Data Production Engineer will support the development and operation of the GPU -accelerated real-time data analysis pipelines that will turn images from the worlds largest digital camera into discoveries. Three years of prototyping efforts have demonstrated the core pipeline architecture and built an archive of representative data; we are now working to build pipelines and platforms that scale to the full array. This scale up involves integration with cloud services distributed storage networks and the dedicated computing cluster supporting Array operations. The Data Production Engineer will bring the real-time analysis pipeline into production working with a team of scientists to develop implement and deploy cutting edge algorithms and approaches to astronomical difference image analysis image resampling and reprojection and coaddition. You will write and design code that interfaces directly with the largest digital sensor array ever assembled a distributed machine vision camera with more pixels than 6000 4K TVs. You will work with a cross-functional team responsible for the entire data path of the Argus Array from the telescope telemetry and hardware operation to long-term data archiving and distribution. Our project management philosophy emphasizes a small and local team; flat management structure; and a highly collaborative working environment. We routinely produce and test prototypes and complex hardware in-house. While you will contribute primarily to the data processing system effort team members frequently collaborate across boundaries and contribute hands-on to various Argus hardware and software subsystems.
Required Qualifications Competencies And Experience
We are searching for an engineer with deep Python expertise (5 years) and demonstrated success in designing and optimizing high-throughput systems (2 years). Experience and proficiency across the software development lifecycle (version control documentation and testing) is required. Experience with GPU acceleration frameworks (Nvidia CUDA PyCUDA CuPy or equivalent) is required.
Preferred Qualifications Competencies And Experience
Experience with maturing research-grade code to production in machine vision astronomical data processing or similar field is preferred. Prior experience translating scientific requirements into technical specifications and working in a mixed research environment is preferred. Experience with cluster-scale and distributed computing in a DevOps context is strongly preferred including working with standard frameworks (Ray Spark Dask or equivalent).
The Argus Array will be the largest optical telescope array ever assembled with a collecting area comparable to the largest monolithic telescopes in the world. The Array will push our observations of the universe into a new regime scanning the sky 100000x faster than current nightly-cadence sky surveys. Argus will capture a continuous multi-color 55-gigapixel movie of the night sky shared with the entire astronomical community in real-time through public transient alerts images and light curves with millions of epochs for hundreds of millions of stars. Joining our local team of astronomers telescope-instrumentalists and engineers the Argus Array Data Production Engineer will support the development and operation of the GPU -accelerated real-time data analysis pipelines that will turn images from the worlds largest digital camera into discoveries. Three years of prototyping efforts have demonstrated the core pipeline architecture and built an archive of representative data; we are now working to build pipelines and platforms that scale to the full array. This scale up involves integration with cloud services distributed storage networks and the dedicated computing cluster supporting Array operations. The Data Production Engineer will bring the real-time analysis pipeline into production working with a team of scientists to develop implement and deploy cutting edge algorithms and approaches to astronomical difference image analysis image resampling and reprojection and coaddition. You will write and design code that interfaces directly with the largest digital sensor array ever assembled a distributed machine vision camera with more pixels than 6000 4K TVs. You will work with a cross-functional team responsible for the entire data path of the Argus Array from the telescope telemetry and hardware operation to long-term data archiving and distribution. Our project management philosophy emphasizes a small and local team; flat management structure; and a highly collaborative working environment. We routinely produce and test prototypes and complex hardware in-house. While you will contribute primarily to the data processing system effort team members frequently collaborate across boundaries and contribute hands-on to various Argus hardware and software subsystems.
Required Qualifications Competencies And Experience
We are searching for an engineer with deep Python expertise (5 years) and demonstrated success in designing and optimizing high-throughput systems (2 years). Experience and proficiency across the software development lifecycle (version control documentation and testing) is required. Experience with GPU acceleration frameworks (Nvidia CUDA PyCUDA CuPy or equivalent) is required.
Preferred Qualifications Competencies And Experience
Experience with maturing research-grade code to production in machine vision astronomical data processing or similar field is preferred. Prior experience translating scientific requirements into technical specifications and working in a mixed research environment is preferred. Experience with cluster-scale and distributed computing in a DevOps context is strongly preferred including working with standard frameworks (Ray Spark Dask or equivalent).
Required Experience:
Staff IC
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
The University of North Carolina at Chapel Hill, the nation’s first public university, is a global higher education leader known for innovative teaching, research and public service. A member of the prestigious Association of American Universities, Carolina regularly ranks as the best ... View more
