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Posted 1 month ago

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Senior Backend Engineering Manager, Recommendations

New York, New YorkHybridFull-time

AI Summary

Senior Backend Engineering Manager leads a team building recommendation services, sets the technical roadmap for the recommender platform, and collaborates with ML, data, and product teams to deliver scalable, low-latency systems.

About this role

Hinge is the dating app designed to be deleted

In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all.

About the Role
At Hinge, the recommendation engine is a central part of our product. Every interaction users have with each other on our app begins with the systems your team builds and owns. As the engineering manager of this team, you will help drive the strategy and execution behind the infrastructure and features that power our recommendations. You’ll work closely with machine learning engineers, product managers, data scientists, and data engineers to build systems that balance personalization, fairness, and user experience at scale, from low-latency match-serving pipelines to the candidate retrieval and ranking systems that determine who users see and when.

Our ability to provide good recommendations is central to achieving trust, engagement, and, most importantly, whether people can find who they’re looking for on Hinge.

Responsibilities

  • Lead, mentor, and grow a team of 6-8 engineers building recommendation services

  • Partner with ML to productionize recommendation models and ensure low-latency, high-availability serving infrastructure

  • Own the technical roadmap for the recommender platform, balancing new capabilities with reliability and performance improvements

  • Drive architecture decisions for recommendation and search infrastructure

  • Establish and maintain engineering standards for code quality, testing, observability, and incident response

  • Collaborate with Product, Design, and cross-functional engineering teams to define and deliver product-facing recommendation features

  • Manage hiring, performance reviews, career development, and team culture

    • What We're Looking For

  • 8+ years of software engineering experience, with 4+ years in an engineering management role

  • Strong backend systems expertise – you've built or operated large-scale distributed systems in production

  • Experience with recommendation systems, search ranking, personalization, or adjacent ML-serving infrastructure

  • Proficiency in one or more backend languages (ideally Go)

  • Familiarity with data processing architectures, feature stores, and model-serving technologies (e.g., Kafka, Spark, ElasticSearch, etc)

  • Track record of hiring, developing, and retaining high-performing engineering teams

  • Ability to communicate technical trade-offs clearly to both engineers and non-technical stakeholders

    • Nice to Have

  • Experience with ML frameworks (TensorFlow, PyTorch) or MLOps tooling (MLflow, Kubeflow, Airflow)

  • Hands-on experience with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes)

  • Background in A/B testing and experimentation platforms

  • Prior work at scale (millions of daily active users or equivalent throughput)

    • Skills

    A/b TestingAirflowAWSAzureBackend SystemsCloud InfrastructureContainer OrchestrationDistributed SystemsElasticsearchExperimentation PlatformsFeature StoresGCPGOKafkaKubeflowKubernetesMLflowMLOps ToolingML Serving InfrastructureModel-serving TechnologiesPersonalizationPyTorchRecommendation SystemsSearch RankingSparkTensorFlow

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