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Build trusted cross-functional relationships with and provide practical and solution-oriented day-to-day commercial legal advice to Hinge finance, accounting, product, engineering and people teams. Support the engagement and implementation of key vendors related to Hinge Engineering, Product and People team operations. Advise and manage workflow process improvement, playbook development, business team training, and template use to address the evolving needs of a growing organization. Assist in administration of corporate policies and procedures, such as vendor security, privacy compliance, and contract approval, along with helping to implement compliance obligations. 4+ years' experience, with both top law firm and in-house legal department experience preferred. Law degree from a top accredited law school and admission (or in-house eligibility) to practice law in New York, Texas or California. Experience drafting and negotiating a range of commercial contracts with domestic and international counterparties, including SaaS and other tech contracts using a \u201cgetting to yes\u201d mentality. Excellent business communication and analytical skills, as well as an impeccable attention to detail and strong sense of ownership and accountability. Comfortable with and interested in using AI tools (e.g., ChatGPT, Gemini, Zoom AI Companion) to enhance drafting, research, and workflow efficiency. Curious and practical-minded legal partner skilled in helping business teams to identify and balance risks against business priorities. Professional ease in working collaboratively with Hinge employees as well as cross-functionally with Match Group's Legal and other shared services functions. A collaborative team player who not only excels in their individual role, but also proactively looks for opportunities to support colleagues, share helpful information, and make processes easier.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/30195407", "isPrivate": false}, {"id": 30194559, "name": "Director, Senior Counsel", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Operations", "t_update": 1756011676, "t_create": 1752172613, "ats_job_id": "470778b7-d2c5-4411-aef5-408754c97049", "display_job_id": "470778b7-d2c5-4411-aef5-408754c97049", "type": "ATS", "id_locale": "1603126930985741675-en", "job_description": "Manage legal support to Hinge's marketing organization with the support of two direct report paralegals. Oversee legal counsel for Hinge's marketing and communications campaigns, promotions and partnerships from conception through execution, including providing advice on advertising laws, regulatory compliance, rights clearances and marketing claims. Serve as a legal lead to Hinge's trust & safety team providing legal counsel and transactional support for customer care and education, tooling and vendor, and QA programs and initiatives. Provide legal counsel to Hinge's user research team, including advising on the design and implementation of research programs. Support Hinge's compliance and regulatory response work, in liaison with Match Group legal, privacy and trust & safety central teams, in connection with state and global regulations such as DSA, UK OSA, EU AI Act and the EU Accessibility Act. Partner cross-functionally with Match Group's privacy, government relations, trust and safety, and communications teams to ensure our internal and external efforts are aligned with Hinge and Match Group's values. Collaborate with internal Match Group (i) intellectual property counsel to support establishing and protecting Hinge's global trademark and IP portfolio, and (ii) litigation counsel to support litigation and regulatory matters. Draft and negotiate commercial agreements, including marketing, SAAS, technology, data processing, agency, content, production, social media, consumer insights, analytics, communications, consulting and other general vendor and operations agreements. Advise and manage workflow process improvement, playbook development, business team training, and template use to address the evolving needs of a growing organization. Assist in the administration of corporate policies and procedures, such as vendor security, privacy compliance, and contract approval. Manage the evolution and implementation of Terms of Use, content policies, disclosures, FAQs, and other user-facing legal policies and information. 7+ years' experience, with both top law firm and in-house legal department experience preferred. Law degree from a top accredited law school and admission (or in-house eligibility) to practice law in New York. Direct experience counseling technology company stakeholders on intellectual property, information security, privacy, biometric and AI regulations in B2C digital contexts such as social discovery platforms, marketplace businesses, user-generated content, and/or regulated products and/or consumer facing technology. Excellent business communication and analytical skills, as well as an impeccable attention to detail and strong sense of ownership and accountability. Comfortable with and interested in using AI tools (e.g., ChatGPT, Gemini, Zoom AI Companion) to enhance drafting, research, and workflow efficiency. Curious and practical-minded legal partner skilled in helping business teams to identify and balance risks against business priorities. Professional ease in working collaboratively with Hinge employees as well as cross-functionally with Match Group's Legal and other shared services functions. A collaborative team player who not only excels in their individual role, but also proactively looks for opportunities to support and mentor colleagues, share helpful information, and make processes easier.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/30194559", "isPrivate": false}, {"id": 28948544, "name": "Senior Data Scientist", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1756011676, "t_create": 1746026132, "ats_job_id": "aeeb9838-ebdb-4a4b-8dec-abbbfd581b8b", "display_job_id": "aeeb9838-ebdb-4a4b-8dec-abbbfd581b8b", "type": "ATS", "id_locale": "6641719287863074600-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 a Data Scientist Strong knowledge of statistics and machine learning Experience with A/B testing Strong working knowledge of SQL and Python (R is acceptable, but we use Python at Hinge) Exposure to engineering best practices in a work environment 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/28948544", "isPrivate": false}, {"id": 27719252, "name": "Staff Machine Learning Platform Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1756011676, "t_create": 1741811827, "ats_job_id": "9ae78f81-e838-4116-9852-07c6c5a6a051", "display_job_id": "R0004338", "type": "ATS", "id_locale": "R0004338-en", "job_description": "Define the long-term, holistic roadmap for the Feature Store platform, aligning it with company-wide ML initiatives and ensuring end-to-end integration with model training, serving and observability platforms. Evaluate and introduce new technologies, tools and best practices that enhance feature serving reliability, scalability, cost efficiency and throughput, including leading build vs buy discussions. Architect, build, and maintain frameworks enabling MLEs for self service data ingestion and serving pipelines for both offline (batch, async) and online (low-latency) feature stores. Partner with cross-functional Platform teams to represent feature engineering requirements and incorporate them into Hinge's wider Platform capabilities. Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand the ML development lifecycle 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 methods, tools and technologies for Feature Engineering. Help design and architect an AI platform that adheres to the principles of responsible AI and simplifies privacy compliance. 5+ years of experience, depending on education, as an ML Platform Engineer, Data Engineer, or Platform Engineer developing and working with large scale, complex data processing and or warehousing systems. 4+ years of experience working on a cloud environment such as GCP, AWS, Azure, and with dev-ops tooling such as Kubernetes 3+ years of experience leading projects with at least 2 other team members through completion. 2+ years of experience for Staff designing and developing online and production grade ML Feature Store 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, particularly data intensive systems. Data engineering expertise: Skills in handling and managing large streaming data processing systems and formats (parquet, json, protobuf, delta) including data cleaning, preprocessing and storage systems. Feature Store Platform technology skills: The ability to establish and use Feature Store platforms such as Databricks, Feast, Tecton, Hopsworks, Ray, and/or similar. Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. ML knowledge: Broad awareness of the entire ML lifecycle, including the data needs for training, serving and evaluation. Communication skills: The ability to communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds through documentation, RFCs and presentations. Software leadership skills: A track record of leading projects with multiple contributors and stakeholders through completion with quantifiable and measurable outcomes. Strategic leadership skills: Demonstrated technical leadership experience in aligning platform strategy with product and business objectives.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/27719252", "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": 1756011676, "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": 19920639, "name": "Senior Machine Learning Engineer, Growth", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1756011676, "t_create": 1704920293, "ats_job_id": "cc9bba44-65fd-43c4-bb19-2dd9a34f62c4", "display_job_id": "R0004268", "type": "ATS", "id_locale": "R0004268-en", "job_description": "Develop and deploy targeting and timing models that underlie a smart notifications system that guides and influences user behavior to improve dating outcomes. Improve user engagement with notifications by optimizing for relevancy and personalizing for responsiveness. Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering impact to our daters. Keep abreast of and bring to Hinge applicable cutting-edge research, technologies, and best practices in the ML/AI space. 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. Proficiency in languages like Python, Java, or C++ Domain expertise: Deep understanding of machine learning model architectures, DNN experience a big plus. Proven track record of building, debugging, and fine-tuning machine learning models for user facing products. System design & architecture: Experience training and deploying large scale ML models especially DNNs. Good understanding of distributed computing for learning and inference. Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with Ray, KubeFlow, or Weights & Biases is a plus. 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 as an MLE, previous experience in User Growth or Monetization is preferred. 2+ years of experience working on a cloud environment such as GCP, AWS, or Azure. 2+ years of experience designing and developing online and production grade ML systems. 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/19920639", "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": 1756011676, "t_create": 1704997239, "ats_job_id": "f6d1cdb5-efcd-4c13-bd51-570568138794", "display_job_id": "f6d1cdb5-efcd-4c13-bd51-570568138794", "type": "ATS", "id_locale": "6203985222364177919-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": 1756011676, "t_create": 1748961320, "ats_job_id": "8e55b4e5-27a4-415c-850a-f3532032c975", "display_job_id": "8e55b4e5-27a4-415c-850a-f3532032c975", "type": "ATS", "id_locale": "2379892612527328112-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. 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": 30513725, "name": "AI Product Manager, Trust & Safety", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1756011676, "t_create": 1753731101, "ats_job_id": "4b3b400d-c147-4cc0-982f-7d430162d839", "display_job_id": "4b3b400d-c147-4cc0-982f-7d430162d839", "type": "ATS", "id_locale": "7191712614212164368-en", "job_description": "Define & enable AI-powered T&S pipelines: Partner with AI engineers to design, prototype, and productionize real-time content moderation and bad-actor detection systems\u2014using LLMs, prompt-engineering frameworks, and vendor platforms like Langfuse. Translate policy into product: Partner with Hinge and Matchgroup's Trust & Safety policy team to adapt and implement our standards via automated workflows covering hate speech, self-harm content, fraud, and more. Lead the full product lifecycle: Drive discovery, set technical requirements, review prototypes, and guide the engineering team through launch and continuous iteration based on analytics and incidents. Set & evolve success metrics: Establish T&S KPIs\u2014moderation throughput, false-positive/negative rates, time-to-resolution, user trust scores\u2014and recalibrate them dynamically across release cycles. Collaborate cross-functionally: Split your time between shaping AI roadmaps (30%) and hands-on product strategy & implementation (70%): working day-to-day with Engineering, Design, Research, Legal, and Operations to align priorities and response plans. Drive rapid experimentation: Own and implement prompt engineering workflows, A/B tests, LLM error analyses, post-mortems, and continuous safety improvements\u2014fostering a culture of data-backed innovation. Own critical decisions: Guide the team on verification thresholds (selfie/ID), reporting workflows, and account actions (warnings, suspensions, escalations). Experience (3+ years): Product management or AI product development in fast-moving startups or startup environments. Technical Acumen: Comfortable partnering deeply with engineers on LLMs, prompt engineering, tracing, and error-analysis tools; able to review model prototypes and guide tuning. Proficiency in Python for prototyping and iterating on portions of our AI services. Hands-on experience with OpenAI APIs (or similar LLM endpoints) and prompt-engineering techniques, like Chain of Thought reasoning, Retrieval Augmented Generation (RAG), and Structured Outputs. Familiarity with LLM tracing/error-analysis platforms (e.g. Langfuse), prompt-engineering libraries, and no/low code tools like n8n. Execution-Oriented: Bias for action\u2014prototyping new workflows; breaking down safety concepts into engineer-friendly requirements, sprint plans, and measurable launches. Collaboration & Communication: Skilled at translating between technical and non-technical stakeholders (Legal, Compliance, Ops); strong documentation and meeting-facilitation skills. Strategic & Adaptable: Thrive in ambiguity\u2014navigate evolving AI tech, shifting threat landscapes, and regulatory changes with startup scrappiness. Passion for Innovation & Safety: Eager to explore cutting-edge AI while building inclusive, trustworthy user experiences. 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Use your expertise in data modeling to design, build, and maintain our analytics data warehouse, which provides clean, accurate, and robust data sets that can be leveraged for reporting, analytics, and machine learning initiatives. Work with stakeholders and translate their needs and expectations into action items and deliverables. Continue to learn more about the Data Engineering discipline, utilize that knowledge in your deliverables, and identify opportunities to enhance our pipelines. Participate in our on-call rotation to ensure system reliability, promptly addressing issues to ensure smooth operations. 5+ years of professional/industry experience Proficient in Python, SQL, DevOps, and databases. 5+ years of professional/industry experience. Experience delivering data products from conception to delivery and with the infrastructure that supports their underlying processes. Experience modeling data sets for different types of sources and business processes. 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