[Haskell] Job Opportunity at Parallel Scientific

[Peter Braam]

Parallel Haskell Programmers

Parallel Scientific, LLC is a Boulder, CO based early stage, but funded
startup company working in the area of scalable parallelization for
scientific and large data computing.  We are implementing radically new
software tools for the creation and optimization of parallel programs
benefiting applications and leveraging modern systems architecture. We
build on our mathematical knowledge, cutting edge programming languages and
our understanding of systems software and hardware.  We are currently
working with the Haskell development team and major HPC laboratories world
wide on libraries and compiler extensions for parallel programming.

Parallel Scientific was founded by Dr Peter Braam in 2010.  Peter formerly
taught mathematics and computer science at Oxford and Carnegie Mellon.
 Then he contributed file systems to Linux and invented Lustre (which
provides storage to 9 of the top 10 systems in the world). He ran several
successful startups, and Parallel Scientific is run by an very experienced
management team and board.

Successful candidates can in some cases work remotely and will work in a
modern virtual environment.  We provide training in advanced processes for
software design and implementation and domain specific knowledge.

Required skills:

   - Very strong background in computer science or mathematics
   - Experience with Haskell
   - Knowledge of systems programming and operating systems functionality
   - Knowledge of system architectures, such as high performance
   networking, memory architectures, multi and manycore CPUs and GPGPUs
   - Experience with performance tuning of parallel or concurrent algorithms
   - Experience designing and implementing concurrent or parallel programs



Experience in one or more of the following areas is desirable:

   - Experience with Haskell compiler technology
   - In depth knowledge of core Haskell libraries for parallel programming
   (NDP, REPA etc)
   - Experience in the area of middleware algorithms for data flow
   programming, graphs, cloud based data analytics, or sparse matrices
   - Domain specific knowledge in scientific programming areas related to
   irregular and sparse problems, e.g. data analytics using graph analysis,
   genomics, tightly connected numerical analysis
   - Experience with performance tuning for parallel applications on multi
   core systems (e.g. with the Intel toolkit), for GPGPU's using Cuda/OpenCL
   or with MPI/OpenMP on clusters of SMPs



To apply, please send a resume to jobs at parsci.com.
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