The Match Recommendations team builds machine learning models that recommend best-match jobs to job seekers on Indeed. The team’s mission is to build the world’s best AI matchmaker that can connect all jobseekers with their next job. To achieve this, the team leverages unparalleled rich data and state-of-the-art machine learning systems to deliver the highest quality matches to jobseekers and employers.
As a Staff Data Scientist on the Match Recommendations team, you will:
- Build highly scalable and performant recommendation systems and technologies that can identify best matches between millions of jobs and millions of job seekers in real-time
- Experiment with POC ML model improvements, scale them to production, and run iterative AB experiments to improve our matching technology
- Represent Indeed at major ML conferences like NeurIPS, ICML, and ICLR
- Mentor and grow other software engineers, data scientists, and ML engineers across teams
- Break down larger ML initiatives into pieces that deliver incremental business value and lead the team to execute on them
Who You Are
You're someone who wants to see the impact of your work making a difference every day. You understand how to use data to make decisions and how to train others to do so. You find passion in the craft and are constantly seeking improvement and better ways to solve tough problems. You produce the highest quality Machine Learning solutions and lead others to do the same. You have high standards and will take pride in Indeed like we do as well as push us to be better. You have delivered challenging technical solutions at scale. You are equally happy talking about deep learning and statistical inference, as you are brainstorming about practical experimental design and technology career development. You love being in the mix technically while providing leadership to your teams.
- 7+ years of industry experience as a Software Engineer, Data Scientist, or Machine Learning Engineer (or 5+ with a PhD or MS)
- Prior success deploying (impactful) Machine Learning solutions to large-scale production systems
- Solid knowledge of data structures and algorithms
- Strong sense of ownership as a technical and product leader
- Excellent communication skills in English, both written and verbal with both technical and business audiences
We get excited about candidates who:
- Have the desire to solve difficult problems at the intersection of machine learning, data engineering, and software engineering
- Have extensive experience and knowledge with cloud technologies (AWS preferred)
- Have search technology experience such as Lucene, Solr and/or Elasticsearch
- Have prior success deploying Recommender Systems / Search Ranking / etc. to large-scale production systems
- Have an advanced degree (PhD or MS) or prior research experience in the fields of machine learning, statistics, or computer science
Who we are
We are a rapidly growing and highly-capable Engineering organization building the most popular job site on the planet. With engineering hubs in Seattle, San Francisco, Austin, Tokyo, Singapore, Hyderabad, Dublin, Aberdeen and Vancouver, we are improving people's lives all around the world, one job search at a time.
As the world’s number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and creating the best experience for job seekers.
(*comScore Total Visits, March 2021)
Salary Range Disclaimer
The base salary range represents the low and high end of the Indeed salary range for this position. Actual salaries will vary and may be above or below the range based on factors including but not limited to location, experience, and performance. The range listed is just one component of Indeed's total compensation package for employees. Other rewards may include quarterly bonuses, long term incentives, an open Paid Time Off policy, and many region-specific benefits.
Salary Range Transparency
SF Bay Area 187,000 - 270,000 USD per year
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