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Build the frameworks to reason rigorously through ecosystem tradeoffs where a win for one cohort reshapes another, and set a vision ambitious enough that the org wants to chase it. Cross-Functional and Industry Leadership: Partner closely with other product groups to integrate AI capabilities across the product and shape roadmap decisions you do not own. Communicate honestly with executive leadership on strategy, tradeoffs, and progress. Own budget and investment strategy for the area, and represent Hinge externally through writing, talks, and community. Technical Leadership: Steer real-time, personalized recommendation systems that reduce ratings per exchange and drive better matches. Bring Generative AI to dating outcomes in ways that are differentiated, authentic, and grounded in how people actually connect. Responsible AI: Hold the bar on scalability, resilience, and rigorous evaluation for both performance and bias. Team and Organizational Development: Structure and scale the team for both deep execution and long-horizon bets. Develop emerging leaders, invest in succession across IC and leadership tracks, and build a culture where rigor, inclusion, and performance reinforce one another. Execution Excellence: Drive predictable delivery, balancing urgent risk response with long-term platform investments. Establish scalable operating rhythms for planning, technical reviews, and incident learnings. 10 or more years across data science, applied ML, and software engineering, with 6 or more years in AI or engineering leadership defining strategy, not just managing execution. A track record of leading real-time, personalized recommendation systems in production, including the relevance, fairness, and scale tradeoffs that carry real consequences. Demonstrated success scaling ML or AI teams and developing technical leaders who carry the work over years, not a single launch. Deep technical fluency across ML, RL, Generative AI, and MLOps, with the communication skills and executive presence to represent AI strategy at the highest levels of the organization. A degree in Computer Science, Machine Learning, or a related quantitative field. A PhD is a plus, not a requirement. Experience building AI systems in a two-sided or constrained marketplace, where optimizing for one group shifts outcomes for another and the right answer is rarely obvious.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "hybrid", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/42409033", "isPrivate": false}, {"id": 40078674, "name": "Lead Product Manager, Platform", "posting_name": "Lead Product Manager, Platform", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1782709375, "t_create": 1770400009, "ats_job_id": "c79d226f-eb60-438c-9d45-b251dbc9d232", "display_job_id": "R0004899", "type": "ATS", "id_locale": "R0004899-en", "job_description": "Define the strategy, roadmap, and success metrics for core platform systems that support multiple product teams across Hinge. 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": 42292407, "name": "Senior Data Scientist, Matching", "posting_name": "Senior Data Scientist, Matching", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1782709375, "t_create": 1780951823, "ats_job_id": "1790127f-d74b-4bf8-bb34-4443f872391d", "display_job_id": "1790127f-d74b-4bf8-bb34-4443f872391d", "type": "ATS", "id_locale": "7553701983824063576-en", "job_description": "Collaborate with a cross-functional team of product managers, researchers, designers and engineers to develop and iterate on product features and strategy Translate product objectives to data science problems and vice versa Apply statistical inference to draw rigorous conclusions from data, especially through designing and analyzing A/B tests and working on strategic insights that drive product strategy Use a combination of exploratory analysis and data mining techniques to generate actionable insights about user experience and user problems Collaborate with AI team to develop, iterate, and test production models (e.g., targeting) 5+ years of experience as data scientist Experience with A/B testing Strong working knowledge of SQL and Python (R is acceptable but we use Python at Hinge) Strong knowledge of statistics and machine learning Superb communication skills Ability to balance rigor with practicality Deep sense of intellectual curiosity Excellent collaboration skills and a track record of cross-functional influence", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/42292407", "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": 1782709375, "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": 1782709375, "t_create": 1704997239, "ats_job_id": "f6d1cdb5-efcd-4c13-bd51-570568138794", "display_job_id": "R0005076", "type": "ATS", "id_locale": "R0005076-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": 42323871, "name": "Director of UX Research, Dating Outcomes & Platform", "posting_name": "Director of UX Research, Dating Outcomes & Platform", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1782709375, "t_create": 1781113133, "ats_job_id": "9a8d4a8f-2880-4399-899b-5c1a20f1f9a4", "display_job_id": "9a8d4a8f-2880-4399-899b-5c1a20f1f9a4", "type": "ATS", "id_locale": "2405418512012034129-en", "job_description": "Define and drive the UX research vision, strategy, and roadmap for Dating Outcomes and Platform \u2014 prioritizing the questions that need to be answered before roadmaps are locked Lead, coach, and grow a team of seasoned, experienced researchers, setting a high bar for craft, rigor, and impact Operate as a strategic partner through synthesizing UXR and DS insights into POVs that shape product vision and strategy and inform executive decisions Represent Dating Outcomes and Platform insights clearly to senior leadership and cross-functional stakeholders, communicating roadmaps, tradeoffs, and product implications Drive cross-team synthesis and frameworks that unify insights across teams and product groups Identify structural and organizational gaps; proactively design ways of working that improve team velocity, cross-functional collaboration, and research quality Build a team culture grounded in curiosity, rigor, deep user empathy - and fun! 10+ years of UX research experience in consumer-facing industries, with 4+ years managing and developing professional researchers across multiple levels. Proven track record of leading research across complex, multi-team consumer product portfolios with clear examples of research directly shaping product strategy and measurable outcomes Deep expertise across qualitative and quantitative research methods \u2014 able to set the methodological bar across a team, partner fluently with Data Science, and integrate quant and qual into a unified research strategy Ability to operate at both the strategic and craft level \u2014 setting research vision while holding a high bar for rigor and execution across the team Experience managing and mentoring highly senior ICs \u2014 able to establish clear roles and responsibilities, protect independent scope, and support researchers who are deeply embedded in product strategy and operating at a level that may match or exceed their manager's domain depth Demonstrated ability to do the organizational glue work: identifying when teams aren't functioning well, diagnosing root causes, and driving the interventions to fix it Confident, clear communicator who can represent research strategy at VP-level forums, influence without authority across product, engineering, design, and data, and present complex tradeoffs accessibly Passion for innovation and exploring how emerging technologies, including generative AI, can elevate the craft and impact of research 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/42323871", "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": 1782709375, "t_create": 1772225821, "ats_job_id": "876b6d08-4893-4c99-9096-cfc3f47e5cf5", "display_job_id": "876b6d08-4893-4c99-9096-cfc3f47e5cf5", "type": "ATS", "id_locale": "4900289683725122-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. 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