Staff Software Engineer, Core Matching & Machine Learning
BumbleOnline Dating company
Austin, United StatesLead
Accel
Greycroft
Blackstone Inc.
Priyanka Chopra Jonas
Data & AI
About the role
TL;DR
Lead the development of Bumble’s recommendations platform using AI and machine learning.
- •Join our team at Bumble, where we’re revolutionizing online dating through innovative AI-driven experiences.
- •We’re seeking machine learning engineers to spearhead the development of the next generation of online dating.
- •Key Responsibilities Own the technical direction for Bumble’s recommendations platform, evolving the systems that service recommendations for millions of members.
- •Lead the design of large-scale distributed systems that power recommendations across multiple teams and domains.
- •Identify and solve the highest-leverage technical problems across the recommendations stack, clarify ambiguous architectural decisions, and create solutions that help multiple teams move faster.
- •Raise the bar for engineering quality through technical leadership.
- •Establish architectural principles, engineering standards, observability practices, and operational excellence that improve the quality and maintainability of systems across the organization.
- •Multiply the impact of other engineers by mentoring senior engineers, influencing technical direction across teams, and sharing context and judgment on the organization’s most challenging engineering problems.
- •Requirements Typically requires 8+ years of building large-scale backend or distributed systems, with experience delivering complex technical initiatives that span multiple teams.
- •Deep expertise in designing and operating high-scale distributed systems, with strong experience in modern languages such as Go, Kotlin, Java, or similar, and a track record of building reliable production platforms.
- •Strong understanding of recommendation systems, ranking architectures, or other large-scale decision systems, including concepts such as retrieval, candidate generation, ranking, feature serving, experimentation, and feedback loops.
- •Experience building cloud-native systems on Google Cloud Platform (GCP) or comparable public cloud infrastructure, with deep knowledge of scalability, resilience, observability, and operational excellence.
- •Demonstrated ability to define technical strategy and influence architectural direction across multiple engineering teams through expertise, collaboration, and sound technical judgment rather than organizational authority.
- •Proven experience partnering closely with Product, Data Science, Machine Learning, and Engineering leadership to translate ambiguous business problems into durable technical solutions.
- •A track record of mentoring senior engineers, raising engineering standards, and creating leverage by improving systems, tooling, architecture, and the effectiveness of the wider engineering organization.
- •Strong AI fluency, using modern AI-assisted engineering tools to improve productivity while applying thoughtful human judgment, maintaining high engineering standards, and ensuring member trust remains central to every technical decision.
Required skills
GoKotlinJavaGoogle CloudKubernetesCI/CDDockerPostgreSQLMySQLMongoDBRedisElasticsearchDynamoDBApache KafkaApache Flink
Nice-to-have skills
Google AnalyticsGA4Looker StudioProduct ManagementAgileScrumKanbanUser ResearchA/B TestingRoadmapping
Domain expertise
fintech
Tech stack
GoKotlinJavaGoogle CloudKubernetesCI/CDDockerPostgreSQLMySQLMongoDBRedisElasticsearchDynamoDBApache KafkaApache FlinkTensorFlowPyTorchscikit-learnHugging FaceNLPLLMsMLflowKubeflowSageMakerVertex AIONNXJAXGitLinuxJira
