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Project manage the Policy team's priorities to drive clarity on complex or novel policy issues. Monitor enforcement trends and decision quality, partnering with Moderation teams to identify policy ambiguity, escalate issues, and refine policy guidance accordingly. Track and report on policy implementation through data dashboards and structured project updates, including the status of policy initiatives (e.g., policy audits, AI policy integration, localization). Own and evolve Hinge's policy documentation processes: ensure version control, documentation standards, and cross-functional visibility. Support policy measurement and iteration by partnering with Data, Product, and Ops to analyze how policies are enforced. Contribute to quality improvement initiatives, including feedback loops with Moderation teams. 5+ years of experience in content moderation, program management, trust & safety, data analytics, or compliance at a global tech platform. Demonstrated success working cross-functionally, particularly in content moderation or AI governance. Strong writing skills; ability to turn complex policy concepts into actionable guidance Familiarity with how policy gets enforced through scaled operations teams and how to track and improve the quality of that enforcement. Proficiency in Looker, Tableau, or SQL. Experience using data and feedback to drive continuous policy iteration. Experience writing scalable policy guidance across global or third-party teams.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/40118764", "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": 1774933352, "t_create": 1770400009, "ats_job_id": "c79d226f-eb60-438c-9d45-b251dbc9d232", "display_job_id": "c79d226f-eb60-438c-9d45-b251dbc9d232", "type": "ATS", "id_locale": "5526502406536352805-en", "job_description": "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. Collaborate with Product, Design, Legal, and Engineering to manage compliance, governance, and best practices related to accessibility. Build systems and processes that make accessibility and design standards easy to adopt, measure, and maintain across teams. Partner with Product Marketing, Trust & Safety, and Growth teams to manage compliance, policy, and global delivery considerations for communication systems. Set and uphold policies for experimentation design and success criteria that enable high-integrity learning across teams. Serve as a platform leader and trusted partner to product teams, helping them leverage design systems and accessibility tooling to ship faster and with higher confidence. 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 working closely with design systems, accessibility initiatives, or UX platforms (direct ownership or deep partnership). Strong technical fluency and comfort collaborating with engineers on shared systems and tooling. 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\u2014and in the platform foundations that enable that mission to scale.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/40078674", "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": 1774933352, "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": 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": 1774933352, "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": 29487638, "name": "Staff AI Engineer", "posting_name": "Staff AI Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1774933352, "t_create": 1748961320, "ats_job_id": "8e55b4e5-27a4-415c-850a-f3532032c975", "display_job_id": "R0004427", "type": "ATS", "id_locale": "R0004427-en", "job_description": "Own the technical roadmap for AI automation across high-volume operational workflows, driving discovery and prioritization of high-impact AI automation opportunities while providing hands-on technical leadership from concept to production. Prototype agentic solutions using the latest platforms and frameworks and integrate them with existing internal and third-party tools and systems. Deliver reliable, scalable, and robust automations with the appropriate evaluations, guardrails, human oversight, and clear performance monitoring. Drive adoption by producing documentation, running hands-on training and enablement sessions for non-technical operators, and curating prompt libraries and playbooks that empower self-service iteration. Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to improving operational efficiency. Embed safety, privacy, auditability, and responsible-AI standards into every workflow in partnership with Legal and Security teams. Mentor and educate ML Engineers and Platform Engineers on new trends and research in AI/ML that can be applied to initiatives to improve user outcomes, promote safety, and improve AI-powered products and workflows. Production-grade agent orchestration and state management: Proven ability to design, build, and operate highly reliable multi-step LLM agents, emphasizing state machine design, reliable tool calling, and recovery from failure states within coordination frameworks. Applied AI engineering & prompt craft: Deep Python skills plus hands-on experience integrating foundation models and crafting robust prompts and utilizing vector databases. Rapid prototyping & experimentation: Proven ability to ship and iterate quickly. Skilled at leveraging fast proofs of concept and early data to drive continuous tuning and feature improvement with high velocity. Backend, data-systems & tool integration: Skilled at wiring external services and internal data into agent workflows through well-designed APIs and schemas. Human-in-the-loop system design: Able to blend automation with human oversight through clear escalation paths, review checkpoints, and moderator tooling. Operator enablement & training: Talent for translating technical workflows into clear, actionable training for non-technical teams and supporting their day-to-day adoption. Working through ambiguity: Proven skill thriving in high-ambiguity, fast-moving environments\u2014prioritizing effectively, adapting plans quickly, and delivering impact amid shifting requirements. 7+ years of software or machine-learning engineering experience, with a recent focus on AI-driven automation or agentic systems. 2+ years delivering solutions that combine automated decision support with human-in-the-loop review. 2+ years designing and tracking operational metrics that demonstrate ROI, accuracy, and user-experience improvements for automated workflows. 1+ years of hands-on experience designing and operating stateful, multi-step agentic workflows (e.g., LangGraph, AutoGen, or similar internal frameworks) in production, moving beyond simple single-turn chatbot or RAG demos. 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/29487638", "isPrivate": false}, {"id": 38964202, "name": "Senior Machine Learning Engineer, Dating Outcomes", "posting_name": "Senior Machine Learning Engineer, Dating Outcomes", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1774933352, "t_create": 1763661427, "ats_job_id": "523e9382-57ad-45bb-a06d-c71e57bd0240", "display_job_id": "523e9382-57ad-45bb-a06d-c71e57bd0240", "type": "ATS", "id_locale": "6816203959448473200-en", "job_description": "Own and contribute to foundational models that power our recommendations ecosystem. Contribute to the research and development of models powering Hinge and experiment with the latest innovations in the field of Machine Learning (e.g., LLM agents, MMoE models, VAEs, etc.) Design, advocate for, and implement solutions that ensure availability, scalability, operational excellence, and cost management, while delivering incremental impact to our daters. Collaborate closely with other Machine Learning engineers, Product Managers, Data Engineers, and Scientists to understand our users' needs and identify opportunities to make their experience better through machine learning. Mentor and educate Machine Learning Engineers on current and SOA research, technologies, and best practices of practicing machine learning at scale. Strong programming skills: Proficiency in languages like Python, Java, or C++ System design & architecture: Proven track record of training and deploying large scale ML models, especially DNNs. 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. 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. 4+ years of experience, depending on education, as a Machine Learning Engineer. 2+ years of experience working in a cloud environment, such as GCP, AWS, or Azure, and with DevOps tooling, including Kubernetes. 2+ years of experience designing and developing online and production grade machine learning systems. 1+ year of experience leading projects with at least 1 other team member through completion. A degree in computer science, engineering, or a related field.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/38964202", "isPrivate": false}, {"id": 39622969, "name": "Lead UX Researcher, Growth", "posting_name": "Lead UX Researcher, Growth", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1774933352, "t_create": 1768426944, "ats_job_id": "7bed0353-9095-4c9f-987f-ee848d9cf467", "display_job_id": "7bed0353-9095-4c9f-987f-ee848d9cf467", "type": "ATS", "id_locale": "6613870294717445949-en", "job_description": "Lead research strategy: Build and drive the research roadmap for Growth product teams, ensuring that research informs product decision making and drives product strategy. Develop and execute end-to-end research: Conduct end-to-end research using appropriate methods that range from strategic to iterative and evaluative to help the team achieve goals. Growth experience: including research into international expansion, monetization and/or merchandising. Building inclusive products: Experience thinking through different audiences' needs, pain points and behaviors, including working with accessibility needs in mind. Being a strategic cross-functional partner: Work in close collaboration with other researchers and cross-functional partners (i.e., product managers, designers, data scientists, customer experience, marketing and brand strategy) to identify key research questions and prioritize projects in the short and long term. Deliver high-impact insights at velocity: Generate actionable insights that help teams make decisions and build momentum towards our mission. Champion culture and clarity: Model honest, empathetic communication and help cross-functional partners navigate ambiguity with confidence and care. 6+ years of user research experience, including 2-3 years of experience in a consumer-facing product research role. Experience with international research in non-US markets Experience working on monetization, subscriptions or new revenue streams or zero-to-one products. Possess strong quantitative (e.g., survey, experimental) skills and expertise with developing frameworks for model measurement.) Strong communicator, committed to telling clear and compelling stories with data. Proficient in data manipulation, analysis, and dashboard creation with R, Python, SPSS, and/or Looker (or similar statistical software.) Proactive at building and sustaining trusting, successful relationships with cross-functional partners (e.g. data science, customer experience, product management, design, engineering, and marketing.) Eager to learn from, collaborate with, and mentor other researchers. 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