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Tinder

Dating app platform with freemium model

Machine Learning Operations Engineer - AI Platform

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeTokyo, JapanNo salary listedHybrid

About the Job

Requirements

  • At least 3 years of professional experience implementing, releasing, and operating commercial applications.
  • Experience developing production applications, including package management, type checking, and testing.
  • Experience creating and operating container images used in production, including writing Dockerfiles and installing middleware.
  • Experience upgrading Kubernetes clusters and operating GitOps using Argo CD, Helm, or Kustomize.
  • Deep understanding of either AWS or Google Cloud, with experience building and operating production infrastructure.
  • Experience responding to incidents and improving systems using metrics, logs, and traces.
  • Experience designing and operating batch and asynchronous processing with idempotency and retries in mind.
  • Experience developing with coding agents and strong motivation to use AI.
  • Ability to understand how authored code behaves in its execution environment, confront incidents, and resolve them hands-on.
  • Ability to prioritize based on product and business value rather than building infrastructure for its own sake.
  • Ability to balance technical ideals with practical constraints and move work forward by reaching agreement with stakeholders.
  • Business-level or higher Japanese and conversational-level or higher English.

Responsibilities

  • Maintain and improve Kubernetes (Amazon EKS) clusters, including version upgrades, node groups, and autoscaling, as well as cluster components managed with GitOps using Argo CD, Helm, and Kustomize.
  • Redesign observability, monitoring, and alerting for AI applications by improving metrics, logs, traces, actionable alerts, and runbooks; automate initial alert investigation using AI agents.
  • Work with the SRE team to define and operate SLI/SLOs for AI applications, set targets based on use-case incident impact, establish burn-rate alerts, and improve cross-team triage flows.
  • Design and operate systems for continuously updating dependencies, Python runtimes, base images, and security patches across Python applications, including automated update bots, lockfile management, and CI validation.
  • Lead migrations as LLM models and SDKs are updated, including generation upgrades for Claude on Amazon Bedrock, GPT models, and Gemini models on Gemini Enterprise Agent Platform; verify quality regressions and release changes gradually.
  • Advance AI infrastructure security and data protection with security and privacy teams, addressing vulnerabilities and permissions in light of supply-chain and AI-enabled attacks, and handling training data and logs according to retention rules.
  • Operate and improve continuous-training pipelines, training environments, and dataset preparation environments using Argo Workflows and Amazon SageMaker.
  • Operate and improve the recommendation training and batch environment on Gemini Enterprise Agent Platform (formerly Vertex AI).
  • Operate Kubernetes-hosted online inference APIs, queue-driven asynchronous workers, and batch applications, including capacity planning, cost optimization, incident response, and improvements to CI/CD and release workflows.
  • Reduce day-to-day development and operations toil using coding agents and AI agents.
  • Build and continually improve harnesses—such as documentation, linting, tests, and CI checks—that let AI agents reference and validate knowledge gained from daily work and implementation.

Desired Qualifications

  • Experience operating production machine-learning model training pipelines or inference services.
  • Experience developing or operating applications incorporating LLMs such as Claude on Amazon Bedrock or Gemini, or experience migrating models.
  • Experience operating workflow engines such as Argo Workflows or Airflow.
  • Experience leading SLI/SLO design and adoption or observability improvements using tools such as Datadog.
  • Experience with infrastructure as code tools such as Terraform.
  • Experience introducing and operating automated dependency updates and security patching, using tools such as Renovate or Dependabot.
  • Experience with software supply-chain security, including dependency and container-image vulnerability management and build or release path protection, or cloud permission design.
  • Experience designing and operating systems for handling personal data according to retention and usage-purpose rules.
  • Experience improving CI/CD or release engineering using tools such as GitHub Actions.
  • Experience automating operations with AI agents, such as incident-investigation support and toil reduction.
  • Experience improving AI-agent work quality over time by preparing agent instructions such as AGENTS.md, linting, and tests.
  • Experience using or operating ML platforms such as Amazon SageMaker or Gemini Enterprise Agent Platform (formerly Vertex AI).
  • Experience building and operating data pipelines using BigQuery or Amazon Athena.
  • Experience with Policy as Code using tools such as OPA Gatekeeper or Conftest.
  • Experience learning new technologies independently and working hands-on across a broad range of areas.

About the Company

Tinder

Dating app platform with freemium model

Tinder is an online dating platform where users swipe right to like or left to pass on profiles, which can lead to matches and conversations. It operates globally with hundreds of millions of users across many countries and languages, using a freemium model with paid tiers (Tinder Plus, Tinder Gold, Tinder Platinum) and in-app purchases for extras like unlimited swipes and the passport feature to swipe around the world. It stands out through its massive global user base, broad language support, a tiered premium structure, and a strong brand presence backed by campaigns and awards. Its goal is to help people meet and start conversations at scale by making it easy to discover potential partners around the world.

Company size
1,001-5,000
Company stage
Early VC
Total funding
$750M
Headquarters
West Hollywood, CA
Founded
2012

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