Where is the Senior Backend Engineering Manager, Recommendations role at Matchgroup located?

The Senior Backend Engineering Manager, Recommendations position at Matchgroup is based in New York, New York. This is an on-site position.

What type of employment is the Senior Backend Engineering Manager, Recommendations role at Matchgroup?

The Senior Backend Engineering Manager, Recommendations position at Matchgroup is a Full time role.

What experience is required for the Senior Backend Engineering Manager, Recommendations role at Matchgroup?

The Senior Backend Engineering Manager, Recommendations position at Matchgroup requires 8+ yrs exp.

What skills are required for the Senior Backend Engineering Manager, Recommendations role at Matchgroup?

Key skills for the Senior Backend Engineering Manager, Recommendations position at Matchgroup include: machine learning, kafka, elasticsearch, tensorflow, pytorch, airflow, aws, google cloud, azure, kubernetes.

Senior Backend Engineering Manager, Recommendations — Matchgroup

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)

Senior Backend Engineering Manager, Recommendations

Job description