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Translate Regulatory Requirements into Product Action: Serve as the bridge between Match Group (legal, privacy, compliance) and Hinge Product, Engineering and Operations teams to define what regulations mean for our platform and how we build for them. Program Manage Compliance Rollouts: Coordinate multi-stakeholder implementation efforts across compliance-related product and operational initiatives. This may include projects tied to user trust, data handling, moderation workflows, and regulatory transparency. Support teams post-handoff and ensure compliance initiatives stay aligned with requirements, timelines, and long-term sustainability goals. Be the Hinge Liaison to Match Group: Represent Hinge's product perspective in safety compliance conversations with Match Group. Provide clarity on feasibility, timelines, and platform constraints, while advocating for workable, user-first solutions. Track and Report Progress: Maintain visibility into compliance project health through internal dashboards, external transparency reporting, and updates to Match Group and Hinge senior leadership. Anticipate What's Next: Stay current on emerging safety and tech platform regulations and advise product teams on roadmap impact. Support Long-Term Compliance Resilience: Lead post-rollout assessments, gap analyses, and sustainability reviews to help Hinge mature its compliance posture. 7-10+ years of experience in compliance program management, technical program management, or trust & safety - ideally in a consumer tech or platform environment. Demonstrated experience leading cross-functional programs with legal, privacy, product, and engineering stakeholders. Experience implementing safety, regulatory, or trust-focused compliance requirements at an online platform is strongly preferred. Comfort working with engineering and product teams, ideally with some background in product thinking or Technical Project or Program management. Ability to quickly develop working knowledge of product architecture, systems, and flows to assess feasibility and unblock projects. Familiarity with digital safety compliance areas like age assurance, content transparency, user data access, or moderation workflows. Ability to interpret regulatory frameworks and connect them to operational and technical realities. Familiarity with global digital safety regulations (e.g. EU DSA, UK Online Safety Act, etc.) Proven ability to scope and drive large, complex, multi-threaded / multi - disciplinary initiatives from ambiguous start to successful delivery. Structured thinker who can operate effectively across a range of workflows, from well-scoped projects to more ambiguous, evolving initiatives that require ongoing clarification and alignment. Executive-level verbal and written communication skills; confident presenting to senior leaders across legal, product, and operations. Ability to synthesize complex requirements and translate them for diverse audiences. Someone who doesn't wait to be told but rather anticipates, investigates, and informs. Willing to go deep into the details to get things done and ensure success.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/39807906", "isPrivate": false}, {"id": 29062284, "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": 1770354094, "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": 39066000, "name": "Lead Product Manager, Account Integrity", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1770354094, "t_create": 1764163494, "ats_job_id": "5c6bd5b6-09ba-4f8c-b12e-34cca9aa58ce", "display_job_id": "R0004723", "type": "ATS", "id_locale": "R0004723-en", "job_description": "Own the end-to-end strategy and execution for authentication, identity, and verification across the Hinge platform Expand adoption of existing verification methods while identifying and launching new, user-friendly approaches Partner closely with cross-functional teammates in engineering, design, data science, and external vendors to deliver impactful experiences Design product solutions that balance simplicity for users with the rigor needed to deter and detect policy-violating actors Evaluate and integrate third-party solutions and vendors, ensuring they align with Hinge's safety, security, and privacy standards Analyze complex metrics and performance signals to guide decisions and continuously improve verification efficacy Advocate for Account Integrity in company-wide strategy and planning efforts, helping shape the roadmap for a safer Hinge 8+ years of experience working as a PM, or relevant experience Proven experience building identity, authentication, or verification products (e.g., age assurance, selfie or ID verification, KYC). Deep understanding of user trust, safety, or abuse-prevention challenges in consumer tech or marketplaces Ability to lead complex, multi-quarter initiatives with clarity, momentum, and alignment Excellent communication, product leadership, and executive presence. Ability to influence decisions and align stakeholders across levels and functions Familiarity with verification vendors and industry best practices; comfortable navigating build vs. buy tradeoffs Exceptional judgment, systems thinking, and ability to make principled tradeoffs in ambiguous spaces", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/39066000", "isPrivate": false}, {"id": 39649231, "name": "Editorial Director", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Marketing", "t_update": 1770354094, "t_create": 1768601973, "ats_job_id": "25a6cb4a-9ac3-4866-980e-bf0b1777e0d1", "display_job_id": "R0004736", "type": "ATS", "id_locale": "R0004736-en", "job_description": "Define and own Hinge's editorial vision and long-term roadmap for owned platforms, ensuring all storytelling consistently reflects our mission, brand values, and distinctive voice. Lead and evolve Hinge Newsroom as a flagship owned platform, overseeing a robust mix of articles, long-form features, Q&As, and narrative storytelling that advances thought leadership, executive visibility, product storytelling, and research- and advice-driven content for daters. Establish and oversee Hinge's technology blog in partnership with cross-functional teams - shaping how we tell credible, human-centered stories about our technology, product principles, and technical innovations. Understand how owned storytelling supports earned media, executive visibility and brand reputation. Translate complex technical concepts, product decisions, and AI developments into clear, accessible, and compelling narratives that build trust with external audiences. Identify, develop, and write culturally relevant content that spotlights Hinge's work, our daters, and the ideas influencing how we build a less lonely world. Set the bar for editorial excellence, writing, editing, and refining content that communicates Hinge's point of view with warmth, clarity, and intention. Ensure all content strengthens trust and emotional connection with our audiences, reinforcing Hinge's thoughtful, human-centered approach and deepening relationships with our community. Develop editorial guidelines and narrative frameworks that help cross-functional partners contribute content that is on-brand, audience-appropriate, and editorially strong. Edit and refine drafts from workstream leaders - enhancing clarity, storytelling, and accessibility without compromising accuracy. Build a fully scaled editorial system - collaborating with Creative, Operations, and Tech partners - to inform blog UX, publishing workflows, standards, and content structure that support consistency, discoverability, readability, and long-term scalability. Partner cross-functionally across Communications, Marketing, Creative, Product, Social Impact, Legal, and Trust & Safety to surface meaningful stories, including interviewing internal or external voices. Ensure a cohesive, consistent expression of Hinge's voice across all owned storytelling channels. Act as a connective leader across teams, aligning narrative, voice, and visual expression to create a unified and intentional storytelling experience at every touchpoint. Serve as a strategic advisor to senior leaders and technical partners on narrative framing, story selection, and editorial best practices. 10+ years of experience in editorial, journalism, or brand storytelling, ideally within mission-driven consumer brands or communications-led organizations. Demonstrated experience building, leading, or evolving an owned storytelling platform, such as a newsroom, editorial site, long-form content series, or similar. Strong experience partnering with Product, Engineering, or Technical teams, with the ability to translate complex concepts into clear, engaging, human stories. Exceptional writing, editing, and narrative leadership skills, with the ability to translate complex ideas into clear, emotionally resonant, human stories. Strong understanding of editorial storytelling as a driver of brand reputation, credibility, and trust. Highly collaborative partner, comfortable working cross-functionally across Communications, Creative, Marketing, and related teams. Equally adept at setting vision and executing with excellence, balancing strategic leadership with hands-on craft. Naturally curious and culturally fluent, with a strong instinct for identifying timely, relevant stories that reinforce Hinge's mission and values. Deep interest in the evolving media landscape, including emerging formats and platforms that create meaningful audience connections. Data-informed storyteller, skilled at using insights and analytics to shape editorial strategy and measure impact. Empathetic, craft-driven leader who values care, clarity, and intention in every piece of content. Experience with product and technology storytelling - translating product principles and innovations into compelling, human-centered narratives.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/39649231", "isPrivate": false}, {"id": 19938972, "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": 1770354094, "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": 29487638, "name": "Staff AI Engineer, Trust & Safety Operations", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1770354094, "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 Moderation, Appeals, and Support 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 Trust & Safety initiatives to promote user safety and improve AI-powered products and workflows. Agentic & workflow-orchestration expertise: Proven ability to design, build, and operate multi-step LLM agents with modern 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: Comfortable shipping quick proofs of concept, running A/B or shadow launches, and iterating based on data. 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, ideally in Trust & Safety, customer support, or adjacent domains. 2+ years designing and tracking operational metrics that demonstrate ROI, accuracy, and user-experience improvements for automated workflows. 1+ years of hands-on work prototyping or operating agentic workflows (e.g., MCP, Agentspace, n8n) in real-world or open-source projects. 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