ML Engineer Lead

2 weeks ago

Tel Aviv, Tel Aviv, Israel Arpeely Full time ₪120,000 - ₪180,000 per year

Come [legally] hack with us the data on the largest exchange that's running our world. Not NASDAQ; the one with way more events - the Global Ads Exchanges, where millions of ads are born and clicked every second. Step behind the curtain of algorithms and competitors that move $1T of annual budgets. Plunge into a world of ISP-volumes of traffic, sub-second predictions, and TBs of live, real-world data. Use cutting-edge analysis, ML, engineering, or just plain hacker-like thinking to out-perform the market.

Arpeely is a Data-Science startup, leveraging data analysis, ML, engineering, and multi-disciplinary thinking to gain a market edge and exploit hidden opportunities in real-time advertising. Processing over 1,000,000 requests per second and serving over 20B sub-second predictions daily, we build and operate Machine Learning algorithms running on the world's largest Real-time-bidding (RTB) Ad-Exchanges.

We are looking for
ML Engineer lead
to join our Data department. In this role, you will be responsible for the infrastructures needed to train models, serve them and do other ML magic.

What You'll Do:

  • Develop, integrate and optimize end-to-end ML solutions (data pipelines, training workflows, and serving infrastructure)
  • Plunge into a world of data, analytics, ML, high-paced and high-scale user and market movements
  • Work closely with Data Scientists to understand the business from top-to-bottom and turn their dreams into reality

Requirements:

  • 4+ years of professional experience in Software Development or Data Science and 2+ years of experience in ML Ops Engineering/Machine Learning Engineering
  • Strong experience with Python and Machine Learning libraries
  • Proficiency with data analysis and feature engineering
  • Experience developing services and APIs in a cloud based microservices ecosystem
  • Experience SQL (BigQuery - Bonus)
  • BSc degree (or higher) in Mathematics, Statistics, Engineering, Computer Science, or any other quantitative field/military experience
  • Team player as well as the ability to be independent and proactive

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