Backend Platform Engineer – Scalable Services, AI/ML Focus

Matchgroup; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Flexible vacation

Volunteer time & donation match

Health, vision, dental

401(k) match + ESPP

Parental leave & family benefits

Professional development stipend

Mental health support

Pet insurance

Commuter subsidy

Tinder Gold

Job summary

Tinder is hiring a mid-level Backend Platform Engineer to design, build, and operate scalable services that power profiles, chat and experiments. You will work with Java, Node.js, Go, or C++, on Kubernetes or ECS, and collaborate across teams to push the platform forward.

You will contribute to a high-scale system, use AWS/GCP/Azure, NoSQL databases, Redis, ElasticSearch, Kafka, Spark, and Docker, while growing with Agile practices and CI/CD.

Qualifications

• BS/MS in Computer Science or equivalent with 2+ years of industry experience.
• Experience with Java, Node.js, Go, or C++.
• Experience with Kubernetes or ECS.
• Experience with AWS, Azure, or Google Cloud Platform.

Responsibilities

• Design, develop and operate scalable, resilient distributed services using Kubernetes or ECS.
• Collaborate with cross-functional teams to expand the service platform.
• Influence team roadmap and product development.
• Mentor and develop other team members.
• Experience with cloud services and NoSQL databases, Redis, ElasticSearch, Kafka, Spark.

Skills

Backend development

CS fundamentals

Distributed systems

Problem solving

Agile & CI/CD

Education

BS/MS in Computer Science

Tools

Kubernetes

ECS

AWS

NoSQL (DynamoDB/Cassandra)

Redis

ElasticSearch

Kafka

Spark

Docker

Typescript

Job description

Tinder is hiring a mid-level Backend Platform Engineer to design, build, and operate scalable services that power profiles, chat and experiments. You will work with Java, Node.js, Go, or C++, on Kubernetes or ECS, and collaborate across teams to push the platform forward.

You will contribute to a high-scale system, use AWS/GCP/Azure, NoSQL databases, Redis, ElasticSearch, Kafka, Spark, and Docker, while growing with Agile practices and CI/CD.