Distributed / Parallel Processing Engineer (Vector-db..

hace 4 semanas

Guadalajara, México HI Technology & Innovation A tiempo completo

**About the Role**:HI Technology & Innovation is collaborating with a pioneering database company to evolve a single-threaded, command-line vector database proof-of-concept, originally written in C#, into a demonstrable, parallelized prototype. We’re looking for an experienced **Distributed or Parallel Processing Engineer** to lead the development of a lightweight “controller + wrapper” layer that adds multi-instance orchestration, parallelism, and query merging capabilities to the current system.This is a high-impact, fast-paced role ideal for someone with strong distributed systems thinking and a pragmatic, get-it-done engineering mindset.**What You’ll Tackle**:- Design and implement a wrapper/controller layer around the existing single-threaded vector DB POC.- Enable **sharding and parallel loading** of large vector datasets across multiple instances.- Expose both**command-line and REST interfaces** to interact with the system.- Output **clear timing metrics** to demonstrate speed-ups from parallel execution.- Deliver a working, testable **prototype**—production-ready polish is not required.**What We’re Looking For**:- ** Deep expertise in distributed computing and parallel processing**, including MapReduce-style design patterns, data sharding, and inter-process communication (IPC).- Proven track record as a **senior engineer** who can work independently, move quickly, and deliver results with mínimal oversight.- Strong problem-solving skills and practical experience building distributed systems and prototypes.- Comfort working across multiple languages and runtimes. Choose **whatever tech stack gets the job done fastest** (Python, C#, C, etc.).- Ability to clearly demonstrate and benchmark performance improvements.**Engagement Snapshot**:- ** Timeline**: Short-term, estimated 5-10 days of focused work.- **Start Date**: ASAP- **Location**: Remote- **Deliverables**: Fully functional parallel prototype with CLI + REST interfaces, benchmark metrics, and sharded query support.

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