hinge jobs in Match Group

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Partner with Design and Engineering to evolve shared components, patterns, and tooling that enable consistent, high-quality experiences across platforms. Lead accessibility initiatives that ensure Hinge meets and exceeds accessibility standards, embedding inclusive design principles into product development workflows. Own governance, standards, and best practices across platform systems, making them easy to adopt, measure, and maintain at scale. Partner with Product, Engineering, Legal, and cross-functional teams to manage compliance, policy, and operational considerations for platform systems. Identify opportunities to improve team velocity through better tooling, documentation, and platform enablement. Serve as a trusted platform leader and collaborator to product managers, marketers, engineers, and executives, clearly communicating roadmaps, rationale, and tradeoffs 8+ years of product management experience, including 3+ years in platform, infrastructure, or enablement-focused roles. Proven track record of owning cross-functional systems or platforms that support multiple product teams. Experience building or scaling internal platforms, developer tools, or shared infrastructure used by multiple teams. Strong technical fluency with the ability to translate between engineering detail and business value. Excellent product judgment with a bias toward scalable, maintainable systems. A consistent track record of cross-functional collaboration with engineering, data science, marketing, and design. A systems-oriented communicator who operates with high autonomy and a deep belief in Hinge's mission to make dating more intentional and in the platform foundations that enable that mission to scale. Fluency with AI tools and a track record of identifying opportunities to embed AI capabilities into platform systems and team workflows. Experience driving AI enablement across cross-functional organizations or helping teams adopt, experiment with, and scale AI-powered tooling effectively.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/40078674", "isPrivate": false}, {"id": 29062284, "name": "Staff Machine Learning Engineer, Growth", "posting_name": "Staff Machine Learning Engineer, Growth", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1777698147, "t_create": 1746481441, "ats_job_id": "9638198d-e429-4945-802c-9c470e1ac692", "display_job_id": "R0004387", "type": "ATS", "id_locale": "R0004387-en", "job_description": "Lead the end-to-end development of production-grade ML systems such as user targeting models that will help drive engagement, improve dating outcomes and/or improve user adoption of and engagement with paid features Define and own the technical roadmap for ML within your product area and align with company-wide priorities Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand their needs and identify opportunities to accelerate the AI/ML development and deployment process Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering impact to our daters incrementally Keep abreast of and bring to Hinge applicable cutting-edge research, technologies, and best practices in the ML/AI space. Mentor and educate ML Engineers on current and up and coming research, technologies and best practices of doing ML at scale. Ensure the ethical and responsible use of ML/AI and compliance with privacy regulations to protect user data Communicate effectively to audiences of various technical and non-technical backgrounds Strong programming skills: Proficiency in Python and ML libraries such as PyTorch Domain expertise: Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning machine learning for user facing products. Experience with causal inference, uplift modeling, and interventional data collection is a plus. System design & architecture: Strong background in setting up and optimizing ML infrastructure, including containerization (Docker), orchestration (Kubernetes), and CI/CD workflows for ML (e.g., model versioning, automated testing). Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, KubeFlow, or Weights & Biases is a plus. Data engineering knowledge: Skills in handling and managing large datasets including data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow. Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.. Software leadership skills: A track record of leading projects through completion with quantifiable and measurable outcomes. 5+ years of experience, depending on education, as an MLE, with at least 2 years in a senior or staff-level role Previous experience in User Growth or Monetization 3+ years of experience designing and developing end-to-end, production grade ML systems 4+ years of experience working in a cloud environment such as GCP, AWS, Azure 3+ years of experience leading projects with at least 1 other team member through completion. A degree in computer science, engineering, or a related field or equivalent experience.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/29062284", "isPrivate": false}, {"id": 19938972, "name": "Senior Machine Learning Platform Engineer", "posting_name": "Senior Machine Learning Platform Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1777698147, "t_create": 1704997239, "ats_job_id": "f6d1cdb5-efcd-4c13-bd51-570568138794", "display_job_id": "R0004668", "type": "ATS", "id_locale": "R0004668-en", "job_description": "Own or contribute to technical designs for the feature platform, training platform, serving platform, and underlying operational infrastructure that provides incremental delivery and impact. Develop, maintain, and enhance reusable frameworks for AI/ML model development and deployment while establishing and driving best practices in machine learning engineering and MLOps. Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering incrementally. Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand their needs and identify opportunities to accelerate the AI/ML development and deployment process. Mentor and educate ML Engineers and Data Scientists on current and up and coming tools and technologies for ML operations through presentations and documentation. Help design and architect an AI platform that adheres to the principles of responsible AI and simplifies privacy compliance. Lead build vs buy discussions on technologies that would underpin the feature, training, and serving layers. Perform other job-related duties as assigned. 3+ years of experience, depending on education, as an ML, backend, data, or platform engineer developing and working with large scale, complex systems. 2+ years of experience working on a cloud environment such as GCP, AWS, Azure, and with dev-ops tooling such as Kubernetes 1+ year of experience leading projects with at least 1 other team member through completion. 1+ year of experience for Senior designing and developing online and production grade ML systems. A degree in computer science, engineering, or a related field. Strong programming skills: Proficiency in languages like Python, Go, or Java. System design & architecture: Ability to design scalable and efficient ML systems. Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. ML knowledge: A basic understanding of ML algorithms, techniques, and best practices. Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.. Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation Software leadership skills: A track record of leading projects through completion with quantifiable and measurable outcomes.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/19938972", "isPrivate": false}, {"id": 41751845, "name": "Senior Backend Engineering Manager, Recommendations", "posting_name": "Senior Backend Engineering Manager, Recommendations", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1777698147, "t_create": 1777412920, "ats_job_id": "553d4da2-ff94-4306-b985-2ea09bf48dca", "display_job_id": "R0004957", "type": "ATS", "id_locale": "R0004957-en", "job_description": "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 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 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)", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/41751845", "isPrivate": false}, {"id": 41194212, "name": "Senior Lead Product Manager, Matching", "posting_name": "Senior Lead Product Manager, Matching", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1777698147, "t_create": 1775151176, "ats_job_id": "72dff6bd-cdc1-4937-b547-827005e3d8df", "display_job_id": "R0004854", "type": "ATS", "id_locale": "R0004854-en", "job_description": "Define how the team thinks about a problem that is still wide open, drive discovery in ambiguous spaces, and push the team to make opinionated bets rather than hedge. Reimagine how preferences work, not as static filters but as a living signal of what someone is actually looking for, balancing user control with what the system is learning over time. Surface the signals that matter, like effort, values, and intentions, so people can quickly understand why a match might be worth their time and feel confident acting on it. Partner closely with data science, machine learning, engineering, design, and research, and work across Recommendations, Growth, and Trust and Safety to create a consistent experience end to end. Communicate strategy, tradeoffs, and progress clearly to senior leadership and align teams around a shared direction. 10+ years of product management experience in consumer tech, with a track record of owning high-impact product areas end to end. Proven ability to lead 0 to 1 product work in ambiguous spaces, turning unclear problems into concrete bets and shipped experiences. Strong intuition for how people form trust, read social signals, and make decisions under uncertainty. Experience in products involving choice, compatibility, or social dynamics is a plus. Comfortable working closely with data science and machine learning teams, with the ability to shape product direction without needing to be deeply technical. Proven results driving measurable improvements to core user outcomes. Exceptional ability to take messy, ambiguous problems and turn them into clear direction that others can execute against. Strong point of view on how AI tools can change how product teams work, and a track record of using them to raise the quality of output.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/41194212", "isPrivate": false}, {"id": 41105641, "name": "Director of Product, Growth", "posting_name": "Director of Product, Growth", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1777698147, "t_create": 1774639523, "ats_job_id": "51501b58-5dd4-43e7-bd4b-aa310502d67e", "display_job_id": "R0004955", "type": "ATS", "id_locale": "R0004955-en", "job_description": "Define and drive the product vision and strategy for User Growth, spanning user acquisition, onboarding, and retention Lead, coach, and grow a team of product managers, setting a high bar for craft, rigor, and impact Own key growth metrics (MAU, registrations, PCR, retention) and drive measurable, compounding outcomes Champion a culture of high-velocity experimentation, setting standards for test design, analysis, and learning across teams Translate user research, qualitative signals, and quantitative data into clear product strategy and prioritization decisions Partner closely with Engineering, Data Science, Design, and Marketing to ship high-quality product experiences Identify and develop new growth loops and channels \u2014 including international expansion, social referral mechanics, and personalization Represent User Growth strategy clearly to senior leadership and cross-functional stakeholders, communicating roadmaps, tradeoffs, and results Build a team culture of curiosity, rigor, and deep user empathy 10+ years of product management experience, with 4+ years managing and developing other PMs Deep experience in consumer growth, acquisition, onboarding, retention, or engagement \u2014 with a strong track record of measurable impact Strong analytical mindset; comfortable driving decisions from data while maintaining sharp product intuition Experience running a high-velocity experimentation culture across a team Proven ability to lead cross-functional teams and influence without authority across engineering, data science, design, and marketing Clear, confident communicator who can operate at both the strategic and tactical level Passion for Hinge's mission of helping people build meaningful relationships", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/41105641", "isPrivate": false}, {"id": 40533079, "name": "Senior Machine Learning Engineer, Trust & Safety", "posting_name": "Senior Machine Learning Engineer, Trust & Safety", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1777698147, "t_create": 1772225821, "ats_job_id": "876b6d08-4893-4c99-9096-cfc3f47e5cf5", "display_job_id": "R0004832", "type": "ATS", "id_locale": "R0004832-en", "job_description": "Develop, deploy, and maintain end-to-end machine learning models to identify and mitigate bad actors, remove policy-violating content, and ensure user safety. Design and implement scalable systems (e.g., using Spark, Kubernetes) to preprocess data, run inference, and manage post-processing pipelines. Define standardized performance metrics, testing protocols, and evaluation processes to measure the effectiveness, identify and mitigate potential risks, and ensure fairness of AI solutions. Ensure ongoing assessment and refinement of AI solutions, incorporating user feedback, business impact, and emerging ethical considerations. Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to user safety. Stay abreast of new trends and research in AI/ML that can be applied to Trust & Safety initiatives to improve detection, user safety, and stay ahead of potential threats. Strong programming skills: Proficiency in languages like Python, Java or C++ and SQL, proficiency in at least one ML stack (e.g., PyTorch), and strong understanding of data pipelines Domain expertise: Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning real-time machine learning models for user facing products. Experience with applying expertise to fraud detection, content moderation, or related fields is a plus . System design & architecture: Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference. Evaluation frameworks for LLMs: Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features. Cloud and data platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with solutions like Databricks, Ray, or KubeFlow is a plus. Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Good understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow. Strategic technical leadership skills: Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives. Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds. Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation. 4+ years of experience, depending on education, as an MLE or data scientist. Previous experience working in Trust & Safety or related fields (e.g., fraud detection, content moderation, compliance) is preferred. 2+ years of experience in applying end-to-end machine learning models, including data collection, model training, deployment, and monitoring in an industry setting 1+ years of experience integrating LLMs in real-world applications with the appropriate baseline metrics and evaluation methodologies. 1+ years of experience utilizing ML infrastructure components such as a feature store, model training environment, model serving environment, observability, workflow orchestrator, etc. A degree in computer science, engineering, or a related field (or equivalent practical experience).", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/40533079", "isPrivate": false}, {"id": 39328100, "name": "Lead Product Designer, Trust and Safety", "posting_name": "Lead Product Designer, Trust and Safety", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1777698147, "t_create": 1766007411, "ats_job_id": "bf0ddf1b-c761-4c5b-bea7-6518e99e0da2", "display_job_id": "R0004721", "type": "ATS", "id_locale": "R0004721-en", "job_description": "Design Leadership and Execution: Lead end-to-end design for safety and trusted connection on Hinge, turning ambiguous problem spaces and strategic direction into thoughtful user flows, prototypes, and high-quality UI. 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Good understanding of distributed computing for learning, data processing, and inference. Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, Databricks, KubeFlow, or W&B is a plus. ML knowledge: Deep understanding of DNN architectures, track record of building, debugging, and fine-tuning models. Familiarity with PyTorch, TF, knowledge distillation, and recommender systems is a plus. DevOps skills: The ability to establish, manage, and use data and compute infrastructure such as Kubernetes and Terraform. Data engineering knowledge: Skills in handling and managing large datasets, including data cleaning, preprocessing, and storage. Deep understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow. 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