Parallel Software Engineer
Mountain View, CA / Hyderabad, IN / Remote
About DataPelago:

DataPelago is at the forefront of revolutionizing data processing for traditional analytics and cutting-edge GenAI preprocessing. We are building an innovative data processing engine that is transforming how Apache Spark, Apache Flink, Ray and others operate on diverse, large-scale data. Our team of engineers drive and adopt advances in hardware-accelerated computing, parallel processing of large-scale data, query optimization, distributed systems, compilers, machine learning, and cloud-native computing. We are looking for specialists to join our engineering team and shape the future of accelerated data processing.
The Opportunity:
As a Parallel Software Engineer, you will be a key individual contributor in developing advanced
parallel software that unlocks the full potential of diverse hardware accelerators including GPUs
and SIMD-capable CPUs. You will enhance functional breadth, performance, scale, and reliability of data processing operators that are integral to our data processing engine. This is a unique opportunity to make a significant impact on a category-defining product and work with a talented team of engineers.
What You'll Do:

• Architect: Influence the architecture of how our data processing engine harnesses the par-
allelism in GPUs and SIMD-capable CPUs efficiently in processing diverse large-scale data.

• Design: Lead design of functional and performance enhancements to operators and func-
tions that are accelerated by our engine.

• Core Development: Individually design, implement, test, optimize, and maintain parallel
implementations of operators and functions on diverse acceleration hardware.

• Innovation and Differentiation: Analyze advances in accelerated computing hardware, pro-
gramming models, and related tools and ensure our engine extends technology and product

leadership.
• Collaboration: Partner effectively with the execution engine engineering team in integrating
parallel software components with the overall engine.
• Continuous Improvement: Foster best practices in design and code reviews, testing, CI/CD,
and issue resolution to maintain highest product quality, security, efficiency, & productivity.
What You'll Bring:

• Bachelor's degree in Computer Science or a related field with 5+ years of relevant experi-
ence OR a Master's degree in Computer Science or a related field with 3+ years of relevant

experience.
• 3+ years of deep technical experience in developing production applications that process
large scale data using SIMD-extensions of CPUs (e.g., AVX), GPU programming models
(e.g., CUDA, ROCm), or equivalent accelerated computing framework.

• Demonstrated experience working with software libraries, development tools, and profiling
tools specific to parallel and accelerated computing.
• Demonstrated experience in troubleshooting and resolving functional and performance
anomalies in both pre- and post-production scenarios.
• Strong knowledge of computer architecture.
• Exceptional programming skills in C, C++.
• Extensive development experience in Linux environments.
• Strong analytical and problem-solving skills with a passion for performance optimization.
Location Considerations:

We value face-to-face collaboration, but recognize that talent can be found anywhere. Our engineer-
ing team works at our headquarters in Mountain View, CA, at our India office in Hyderabad, and at

remote locations.
Why Join DataPelago?

• Technology Leadership: Shape the architecture and development of core parallel data pro-
cessing functions of our engine.

• Cutting-Edge Innovation: Work on challenging problems at the forefront of accelerated
computing and data processing.
• Significant Impact: Your contributions will directly impact the performance and scalability
of our mission-critical platform.
• Growth: Expand your technical expertise and scope of responsibilities working with other
talented engineers and with a growing product.

• Competitive compensation, stock options, comprehensive benefits package, leadership de-
velopment opportunities.