Haskell - Reactive Streams for Big data & Systems programming

We are looking for engineers with extensive experience with Reactive Stream-based programming to build tooling for a stream library in Haskell.

We are building Realtime data processing systems using Haskell Streamly. Streamly is a high-performance library with Stream fusion, inlining and custom memory management (outside the GC), making it achieve performance gains that are impossible do with JVM based frameworks.

We are looking for Haskell / Scala engineers with deep expertise in stream-based programming - Flink, Spark Streaming, Akka Streams, RxJS etc. , to help us with these projects

- Add telemetry/stream monitoring infrastructure using Prometheus
- Add backpressure support in Streamly
- Add interfaces to Timeseries DBs (TimescaleDB, ClickHouse) and other systems like Redis Streams
- Add stream persistence in local disk
- Add master/worker topology for stream processing - master divides a single stream and uses workers as compute processors

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In addition to big data processing, we are also going to use Streamly for systems programming like - writing API rate limiters, Proxies that help in intelligently routing traffic, Intelligent infra auto scalers, Intelligent turn on/off, rerouting rule execution based on realtime data.

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People who would like to do high scale engineering & practical production work with FP/Haskell can apply. Thanks!
About the recuiter
Member since Sep 4, 2017
Penelope
from Bangkok, Thailand

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Offer to work on this project closes in 40 days!
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