Senior Machine Learning Engineer, Trust & Safety at Tinder (Greater LA Area, CA)
| Greater LA Area
Sorry, this job was removed at 3:07 a.m. (PST) on Wednesday, February 23, 2022
Tinder connects people. With tens of millions of members and a presence in every country on earth, our reach is expansive — and rapidly growing. Your daily work here will cause millions of people to spark new and meaningful connections. Our small, dedicated engineering team has one of the highest ratios of members to engineers in the industry, which makes every member of the team critical to our success. You'll have a unique opportunity to join a company with a global footprint while working on a team that's small enough for you to feel the impact each day.
Tinder T&S team is responsible for systems, algorithms, and policies that keep Tinder and its members safe. It is a multi-disciplinary team of Engineers, ML Practitioners, and Policy Experts.
In This Role, You Will:
- Own, improve, and set the road-map of existing media(video/images/audio) moderation systems.
- Identify new opportunities, and develop those opportunities into valuable focus areas within the machine learning team.
- Build models, and algorithms to improve T&S at Tinder.
- Work closely with engineering teams, product teams.
- Deliver solutions in the existing tech stack.
What We're Looking For:
- Shines when working, and communicating with other teams, and stakeholders. Thrives on driving consensus across varied viewpoints.
- Have the ability to take complex high-level guidance, learn quickly, define actionable milestones across partner teams, and deliver.
- Takes pride in polishing and supporting engineering systems, and products and enjoys delivering well-engineered systems as much as well-trained models.
- BS/MS/Ph.D in Computer Science or related field.
- 3+ years experience of building production ML systems in the computer vision domain.
- Proficiency in Python.
- Proficiency in Tensorflow, or PyTorch.
- Experience with data processing frameworks like Spark.
- Experience with K8s, Docker, GPUs, and Linux based systems.
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