Senior Backend Engineering Manager, Recommendations

Role Summary

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

As a member of our team, you’ll enjoy

• 401(k) Matching: We match 100% of the first 10% of pre-tax 401(k) contributions you make, up to a maximum of $10,000 per year.
• Professional Growth: Get an annual Learning & Development stipend once you’ve been with us for three months. You also get free access to Udemy, an online learning and teaching marketplace with over 6000 courses, starting your first day.
• Parental Leave & Planning: When you become a new parent, you’re eligible for 100% paid parental leave (20 paid weeks for both birth and non-birth parents.)
• Fertility Support: You’ll get easy access to fertility care through Carrot, from basic treatments to fertility preservation. We also provide a stipend towards fertility preservation. You and your spouse/domestic partner are both eligible.
• Date Stipend: All Hinge employees receive a $100 monthly stipend for epic dates– Romantic or otherwise. Hinge Premium is also free for employees and their loved ones.
• ERGs: We have eight Employee Resource Groups (ERGs)—Asian, Unapologetic, Disability, LGBTQIA+, R aices , Women/Nonbinary, Parents —that hold regular meetings, host events, and provide dedicated support to the organization & its community.

At Hinge, our core values are…

• Authenticity: We share, never hide, our words, actions and intentions.
• Courage: We embrace lofty goals and tough challenges.
• Empathy: We deeply consider the perspective of others.

Diversity inspires innovation

Hinge is an equal-opportunity employer. We value diversity at our company and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds.

• If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please let your Talent Acquisition partner know.
• #Hinge

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

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)