Why work at Voltron Data?
- We’re Going for Impact: We are a Series A, venture-backed startup assembling a global team to build a new foundation for data analytics with Apache Arrow. This foundation will usher in a wave of innovation in data processing that can take full advantage of the speed and efficiency offered by modern hardware.
- We’re Committed to Bridging Open Source Communities: We are a collection of open source maintainers who have been driving open source ecosystems over the last 15 years, particularly in the C++, Python, and R programming ecosystems.
- We’re Building a Diverse, Inclusive Company: We are creating a representative, equitable, and respectful workplace that prioritizes employee growth. Everyone at Voltron Data is bought into the company’s success; all voices are critical to shaping the organization’s future.
Timeline
Below is a rough timeline of where you can expect to be at different points during your career path starting in this position.
Upon joining:
- Spending time learning about the Apache Arrow memory layout, compute primitives, and APIs.
- Learning and embracing the Apache development process.
- Familiarizing yourself with the different partners for compute on Apache Arrow.
Within a month:
- Implementing new high performance vectorized compute kernels.
- Optimizing performance of existing compute kernels.
- Participating in peer code review in Compute Kernel development.
- Contributing to technical discussions and technical design documents.
- Reviewing SIMD Libraries for targeting multiple CPU architectures.
- Architecting / Designing performant compute kernels that use SIMD instructions.
- Leading technical discussions, building technical design documents, and reviewing work in Kernel development.
- Collaborating with other teams at Voltron Data to ensure that compute kernel APIs can be utilized as effectively and efficiently as possible.
- Collaborating with the open source Apache Arrow ecosystem to make Arrow the most performant data analytics solution possible.
Within 6 months:
- Developing a comprehensive set of low level benchmarks for to enable observing and addressing performance regressions.
- Ensuring that the compute kernels are compatible and performant across platforms (Linux, MacOS, and Windows).
- Identifying and building reusable components and primitives across different functions to ensure a high quality and maintainable codebase.
- Architecting / Designing a plan to support multiple platforms with compute kernels (Linux, MacOS, and Windows).
- Helping to balance development prioritization between development of new kernels and optimization of existing kernels.
- Designing process to ensure kernels are consistently improving in performance.
- Working with benchmarking team to ensure all performance concerns are addressed.
Within 12 months:
- Analyzing compute kernels implementations to identify inefficiencies and designing solutions to address those inefficiencies.
- Continuing to build out the collection of compute kernels to ensure they are as high quality as possible, balancing performance, usability, and maintainability.
- Acting as a compute kernels tech leader within Voltron Data.
- Defining standard methodologies for compute kernel development and promoting these across the Voltron Data and Apache Arrow ecosystems.
- Ensuring that the compute kernels are as high quality as possible, balancing performance, usability, and maintainability.
Previous experience that could be helpful:
- Building libraries in C++, especially using Modern C++.
- Building and/or using performance portability libraries on accelerator hardware.
- Building distributed algorithms and libraries.
- Building libraries that target network acceleration hardware.
- Building throughput optimized, IO-intensive libraries and/or applications.
- Writing and/or optimizing code using CPU SIMD intrinsics, CUDA, ROCm, SYCL, OpenCL, or other hardware performant languages.
- Using and/or building performance portability libraries on accelerator hardware.
Additional Information:
The expected salary range is $165,000 to $220,000 + equity + benefits. Actual starting pay will be based on job-related factors, including exact work location, experience, training, and skill level, so may be higher or lower than what is shown on this posting.
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