Senior Machine Learning Engineer, Trust and Safety

Key Skills

AWS, Azure, Computer Vision (CV), Docker, GoLang, Google Cloud Platform (GCP), Java Programming, Kubernetes-K8s, Linux Operating system, Machine learning techniques, matplotlib, Natural Language Processing (NLP), NumPy, Pandas, Python Programming, PyTorch, Scala Programming, Statistical modeling, TensorFlow, Unix Operating system

Job Description

The Team

The Engineering team is responsible for building innovative features and resilient systems that bring people together. We're always experimenting with new features to engage with our members. Although we are a high-scale tech company, the member-to-engineer ratio is very high—making the level of impact each engineer gets to have at Tinder enormous.

Tinder Trust & Safety team is responsible for systems, algorithms, and policies that keep Tinder and its members safe. It is a multi-disciplinary team of Machine Learning engineers and Anti-Abuse Data Analysts.

Where you’ll work:This is a hybrid role and requires in-office collaboration twice per week. This position is located in Los Angeles, San Francisco, and/or Palo Alto, CA.

In this role, you will:

• Design, improve and own our existing bad-actor detection and escalation systems, which are based on both rules and multi-modal ML models.
• Identify new opportunities in the current systems, and develop solutions from prototype to production.
• Work cross functionally and deliver solutions based on the existing tech stack.
• Lead and mentor other members on the team from technical perspectives.

You’ll need:

• 5+ years of professional experience in building large scale production ML systems, including all phases of an end-to-end ML pipeline.
• Deep understanding in Machine Learning, particularly in deep learning applied in NLP, Computer Vision and Classification.
• Hands-on experience and proficient in one or multiple modern ML frameworks, such as Tensorflow, Keras, PyTorch, etc., as well as in popular data science Python libraries, such as NumPy, Pandas, Matplotlib, etc.
• Proficient in data analysis with SQL.
• Familiar with Unix/Linux based development environments.
• Strong communication skills and the ability to work well cross-functionally.

Nice to have:

• Prior experience in the Trust and Safety / fraudulent detection problem space, highly preferred.
• Familiar with data processing frameworks, such as Spark.
• Prior experience in distributed large scale, low latency serving systems.
• Hands-on experience in one or more backend programming languages besides Python, such as Java, Scala, Go, etc.
• Familiar with cloud based computing platforms (AWS, GCP, Azure) and container technologies (Docker, Kubernetes).
• S. / Ph.D in Computer Science, Computer Engineering, Applied Math, Physics, Statistics or a related STEM field.

As a full-time employee, you’ll enjoy:

• Unlimited PTO (with no waiting period), 10 annual Wellness Days
• Time off to volunteer and charitable donations matched up to $15,000 annually
• Comprehensive health, vision, and dental coverage
• 100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP)
• 100% paid parental leave (including for non-birthing parents) and family forming benefits
• Investment in your development: mentorship through our MentorMatch program, access to 6,000+ online courses through Udemy, and an annual $3,000 stipend for your professional development
• Investment in your wellness: access to mental health support via Modern Health, paid concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy
• $500 work-from-home stipend to set you up for remote work
• Free subscription to Tinder Gold

$170,000-$210,000 a year

Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.