Created about 2 months ago
Snagajob Snagajob

Machine Learning Engineer at Snagajob

Remote in USA

  • Wayner Barrios
  • Remy Lagrois
  • Juan Manuel Ciro Torres
  • Nader Sarsour
  • Noha Ahmad
  • Caroline
  • Christian
61 Applicants

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Job details

These are the details of the job, consider each of them before you apply.

  • Company: Snagajob
  • Salary: Salary to be Agreed
  • Remote?: Yes

Job Description:

The Opportunity

In an effort to better serve our 47 million registered hourly workers and over 450,000 employer locations, Snagajob’s Data Science team is looking for a Machine Learning Engineer to deploy and optimize predictive pipelines and help fulfill our mission of helping people find their best fit job. The Data Science team at Snagajob includes a heavy emphasis on search, information retrieval, matching, and recommendation, as well as performance tuning at scale and ensuring model integrity. This role provides an excellent opportunity to make a direct impact in a meaningful customer-facing product. 

Our tech stack includes Python (pandas, numpy, sklearn, pytorch, flask), AWS (EC2/ECS, S3, EMR, Sagemaker), Elasticsearch, Mongo, CircleCi, Docker, Terraform, and other technologies. You might not have experience in every area but if you have a drive to learn and grow, we encourage you to apply.

This role may be based remotely or in our Arlington or Richmond, VA or Charleston, SC office. 

What Snagajob Can Promise You

When you join the Snagajob Engineering team, you’ll be working on a high-volume, high-traffic site that gets over 50 million visits a month! But that’s just the start of it. You get to contribute more than just code; we have a highly collaborative environment, so you’ll influence what we build and how we build it. Expand your skills with our weekly tech talks. Learn about, and experiment with, new technologies/ideas in our monthly hack days and chapter meetings. Engineering at Snagajob isn’t just about keeping the lights on and the site running. It’s a place for you to learn and grow in a supportive team environment.

What You’ll Get to Do

  • Implement, optimize and tune data science models and pipelines that are highly available, scalable, and reliable
  • Collaborate with data scientists, data engineers, and product managers to integrate and validate Machine Learning solutions end to end
  • Partner with product teams to measure and improve product KPIs
  • Support and improve existing data science pipelines and systems in production 
  • Test and implement algorithms in scalable, product-ready code
  • Research and recommend platforms, tools and industry best practices to improve efficiency and quality of Machine Learning implementations 
What You'll Bring

  • Advanced degree, or equivalent experience, in computer science, mathematics, or a closely related field - with a concentration in Machine Learning
  • Extensive experience measuring and improving performance of Machine Learning services
  • Production experience in event-based architectures (Kafka, Confluent, etc.), REST interfaces, data pipelines and other real-time strategies
  • Experience deploying and automating models using common Machine Learning frameworks such as scikit-learn, PyTorch
  • Ability to integrate data science environment with platform software architectures
  • Experience working with relational, NoSQL, and/or graph databases
  • Familiarity working in Linux-based systems and/or cloud computing resources, especially AWS
  • Experience building and maintaining production knowledge graphs, search ranking, text classification and/or recommendation systems
  • The ability to live by Snagajob’s core values - solidarity, candor, unconvention, fire - by being an ally, speaking hard truths, questioning the status quo, and always doing whatever it takes to meet our mission of putting people in the right-fit positions so they can maximize their potential and live more fulfilling lives 
Bonus Points

  • Experience processing customer engagement clickstream data
  • Experience designing and implementing A/B testing strategies 
  • Experience working with search and information retrieval systems such as SolR/Elasticsearch, as well as experience with information retrieval success metrics

Hiring policy
The personal data you provide as an applicant to Snagajob through this website, shall be transferred by such receiver to Snagajob under our terms and conditions for application purposes. Consequently, by sending your information through of the website, you consent to the transfer of personal data to third parties, in compliance with the provisions of the Laws for the Protection of Personal Data from each country where has a presence, as the consent is free, prior, express, unequivocal and informed.
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