Senior Backend Engineering Manager, Recommendations

About the role

Hinge is the dating app designed to be deleted. We aim to inspire intimate connections and create a less lonely world. Our success is measured by the number of great dates set up.

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

Requirements

• 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

Qualifications

• 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)