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HomeCompaniesMatch GroupSenior Backend Engineering Manager, Recommendations

Senior Backend Engineering Manager, Recommendations

Match Group · New York, New York · Hybrid · Active · $219,000–$263,000 / year · Lever

Job facts

FieldValue
CompanyMatch Group
TitleSenior Backend Engineering Manager, Recommendations
Normalized title-
Department / teamHinge / Engineering
LocationNew York, NY, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary$219,000–$263,000 / year
Statusactive
ATS providerLever
Posted / first seen2026-04-28 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-18

Related slices

PageWhat it containsOpen
Company jobsActive postings from Match Group.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Lever.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in New York.Open
Department jobsActive postings in Hinge.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyMatch Group
Sourcecad27147-ba1a-4e3d-8008-1d5aa12d0cd7
ATS providerLever

Description

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. 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+, Raices, 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 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)

Full job record

Job IDccf191f6bea31ce0f7051e67e406c382f729f1f1
Org IDebc47b6a-8876-45bc-885d-50880fc283e3
Source IDcad27147-ba1a-4e3d-8008-1d5aa12d0cd7
Board IDcad27147-ba1a-4e3d-8008-1d5aa12d0cd7
Providerlever
Provider Job Key553d4da2-ff94-4306-b985-2ea09bf48dca
TitleSenior Backend Engineering Manager, Recommendations
Normalized Title
Statusactive
Activeyes
Location TextNew York, New York
DepartmentHinge
TeamEngineering
Employment TypeFull-time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionNY
CityNew York
Salary RawUSD 219000-263000 per-year-salary
Salary Min219,000
Salary Max263,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.lever.co/matchgroup/553d4da2-ff94-4306-b985-2ea09bf48dca
Apply URLhttps://jobs.lever.co/matchgroup/553d4da2-ff94-4306-b985-2ea09bf48dca/apply
First Seen At2026-05-29 07:07:24Z
Last Seen At2026-06-18 07:57:17Z
Last Checked At2026-06-18 07:57:17Z
Last Changed At2026-05-29 07:07:24Z
Inactive At
Source Posted At2026-04-28 21:48:40Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=lever/board=matchgroup/date=2026-06-18/2026-06-18T07-57-16-691Z-2e4a33647ebf652f7fcc9df50da9df14760b2018c2834efe816e9277a0d30783.json
Event Fields
{
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  "source_hash": "e63f10a11a87579705b8151a6b6447deae0d9bc1c979ff77a2df9482f6980791",
  "last_changed_at": "2026-05-29T07:07:24.833Z",
  "active_status": "active"
}
Parsed Structured
{
  "language": "en",
  "location": {
    "raw": "New York, New York",
    "city": "New York",
    "region": "NY",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.85
  },
  "salary_max": 263000,
  "salary_min": 219000,
  "inferred_at": "2026-06-18T07:57:17.526Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "New York, New York",
      "city": "New York",
      "region": "NY",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.85
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": "hybrid",
  "salary_period": "year",
  "workplace_type": "hybrid",
  "salary_currency": "USD"
}
Extensions
{}
Native Structured
{
  "lists": [
    {
      "text": "Responsibilities",
      "content": "\n<li>\n<p>Lead, mentor, and grow a team of 6-8 engineers building recommendation services</p>\n</li>\n<li>\n<p>Partner with ML to productionize recommendation models and ensure low-latency, high-availability serving infrastructure</p>\n</li>\n<li>\n<p>Own the technical roadmap for the recommender platform, balancing new capabilities with reliability and performance improvements</p>\n</li>\n<li>\n<p>Drive architecture decisions for recommendation and search infrastructure</p>\n</li>\n<li>\n<p>Establish and maintain engineering standards for code quality, testing, observability, and incident response</p>\n</li>\n<li>\n<p>Collaborate with Product, Design, and cross-functional engineering teams to define and deliver product-facing recommendation features</p>\n</li>\n<li>\n<p>Manage hiring, performance reviews, career development, and team culture</p>\n</li>\n"
    },
    {
      "text": "What We're Looking For",
      "content": "\n<li>\n<p><strong>8+ years</strong> of software engineering experience, with <strong>4+ years</strong> in an engineering management role</p>\n</li>\n<li>\n<p>Strong backend systems expertise – you've built or operated large-scale distributed systems in production</p>\n</li>\n<li>\n<p>Experience with recommendation systems, search ranking, personalization, or adjacent ML-serving infrastructure</p>\n</li>\n<li>\n<p>Proficiency in one or more backend languages (ideally Go)</p>\n</li>\n<li>\n<p>Familiarity with data processing architectures, feature stores, and model-serving technologies (e.g., Kafka, Spark, ElasticSearch, etc)</p>\n</li>\n<li>\n<p>Track record of hiring, developing, and retaining high-performing engineering teams</p>\n</li>\n<li>\n<p>Ability to communicate technical trade-offs clearly to both engineers and non-technical stakeholders</p>\n</li>\n\n<div>&nbsp;</div>\n<div>&nbsp;</div>\n<div><strong>Nice to Have</strong></div>\n<div>\n\n<li>\n<p>Experience with ML frameworks (TensorFlow, PyTorch) or MLOps tooling (MLflow, Kubeflow, Airflow)</p>\n</li>\n<li>\n<p>Hands-on experience with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes)</p>\n</li>\n<li>\n<p>Background in A/B testing and experimentation platforms</p>\n</li>\n<li>\n<p>Prior work at scale (millions of daily active users or equivalent throughput)</p>\n</li>\n\n</div>"
    }
  ],
  "country": "US",
  "createdAt": 1777412920977,
  "updatedAt": null,
  "categories": {
    "team": "Engineering",
    "location": "New York, New York",
    "commitment": "Full-time",
    "department": "Hinge",
    "allLocations": [
      "New York, New York"
    ]
  },
  "salaryRange": {
    "max": 263000,
    "min": 219000,
    "currency": "USD",
    "interval": "per-year-salary"
  },
  "workplaceType": "hybrid"
}
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