Senior Data Engineer (Machine Learning)

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Golden Careers Recruitment
  • Post Date: 30/08/2021
  • Views 87
Job Overview

Job Description

Our client is a technology company making AI-driven software that increases their clients’ business impact, so they can deliver the sales, support and marketing their customers want.

They are looking to recruit a Senior Data Engineer (Machine Learning) who will work within its in-house Artificial Intelligence Team to undertake this challenging role and push the limits of Artificial Intelligence through innovative products and solutions that solve business problems in real life.

Job Responsibilities

  • Develop and maintain production grade ML infrastructure: speech recognition, text analysis, auto ML
  • Build data pipelines for data scientists
  • Develop and maintain internal tools for data scientists (data processing, metrics, external systems integrations)
  • Design AI services architecture (specifications, POCs)
  • Contribute to project planning including new features and AI products roadmap
  • Integrate AI services with other company products
  • Collaborate with Data Scientists and DevOps team
  • Participate in code review and team meetings
  • Coach and mentor fellow Data Engineers

Requirements

  • BSc/MSc in computer science, applied mathematics or relevant working experience
  • Production experience in large scale ML systems (>2 years)
  • Good understanding of classical algorithms and data structures
  • Strong knowledge of and experience in at least one of the following: Python, Golang, C/C++
  • Strong knowledge of and production experience in actual python stack (any popular framework: Flask, Django, etc)
  • Good understanding of and production experience in relational databases (e.g. PostgreSQL)
  • Strong problem solving and critical thinking
  • Team worker and lifelong learner

Desirable

  • Good understanding of and production experience in some of the following NoSQL/NewSQL databases (Redis, MongoDB, ClickHouse, Vertica, Druid, any exotic DB are welcome)
  • Familiarity with distributed databases and distributed systems
  • Familiarity with at least one of the following: Apache Kafka, Apache Airflow , Apache Spark
  • Familiarity with modern DevOps stack (Docker, Kubernetes)
  • Familiarity with Machine Learning basics (e.g. knowing the difference between classification and regression)
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