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At least 5 years of professional experience in application security. A track record of manually testing for and identifying impactful vulnerabilities. The ability to effectively partner and communicate with Engineering and Product teams. Experience securing large-scale web/mobile applications, including performing security code reviews, vulnerability assessments, and manual testing for logic flaws. Experience with various prompt engineering techniques and AI models to effectively develop tooling. Ability to write clean and maintainable code integrating across various systems. Experience publicly writing about or presenting security related work. Bachelor's Degree in Computing Science or related field. 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The ability to effectively partner and communicate with Engineering and Product teams. Experience securing large-scale web/mobile applications, including performing security code reviews, vulnerability assessments, and manual testing for logic flaws. Experience with various prompt engineering techniques and AI models to effectively develop tooling. Ability to write clean and maintainable code integrating across various systems. Experience publicly writing about or presenting security related work. Bachelor's Degree in Computing Science or related field. Develop tooling leveraging AI to identify security vulnerabilities in code and configuration oversights.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "remote_local", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/30205095", "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": 1758171675, "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": 30195407, "name": "Corporate Counsel", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Operations", "t_update": 1758171675, "t_create": 1752172743, "ats_job_id": "cb3a3c28-5940-4251-b583-c32262329dad", "display_job_id": "cb3a3c28-5940-4251-b583-c32262329dad", "type": "ATS", "id_locale": "2812590576916538796-en", "job_description": "Draft, revise and negotiate various commercial agreements, including SaaS, technology, payments, analytics, research, licensing, development, product integration, data processing, events, production, recruiting, independent contractor, consulting, and other general vendor and operations agreements. 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": 20079076, "name": "Machine Learning Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1758171675, "t_create": 1705101155, "ats_job_id": "3fc3a7d4-4a84-4eb9-80d6-ab3c549c6171", "display_job_id": "3fc3a7d4-4a84-4eb9-80d6-ab3c549c6171", "type": "ATS", "id_locale": "203998211731315363-en", "job_description": "Own and contribute to foundational models (e.g. CLIP embeddings) that powers our recommendations pipelines. Contribute to the research and development of recommender models as well experiment with the latest ML innovations (e.g. LLM agents and transcription models) Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering impact to our daters 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 on current and up and coming research, technologies and best practices of doing ML at scale. Perform other job-related duties as assigned. 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 specially 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 ML serving solutions like Ray, 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, recommender systems are a plus. Dev-ops skills: The ability to establish, manage, and use data and compute infrastructure such as Kubenetes 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 an MLE. 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. 2+ years of experience for Senior designing and developing online and production grade ML systems. 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/20079076", "isPrivate": false}, {"id": 29613669, "name": "Lead Product Manager, Recommendations", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1758171675, "t_create": 1749676109, "ats_job_id": "da192775-c278-4906-8776-204d7032c291", "display_job_id": "R0004388", "type": "ATS", "id_locale": "R0004388-en", "job_description": "Define the product strategy. Set the long-term vision for recommendations, secure executive alignment, and bring clarity to a space that touches nearly every team and user. Own the roadmap. Translate strategy into a clear, focused roadmap. Prioritize the most important work, make smart tradeoffs, and keep partners aligned as priorities evolve. Communicate with clarity and influence. Own the narrative around plans, priorities, and decisions, whether you're reviewing tradeoffs with an engineer or presenting next steps to executive leadership. Develop features that shape dating. Own and evolve how we model, rank, and personalize recommendations. Lead your team through the full product development cycle, from research to concept to experiment to launch. Partner with UI-focused product and design teams to build a discovery experience that feels useful, personal, and emotionally intuitive. Make decisions grounded in insight. Use experiments, behavioral data, and research to guide decisions, while navigating ambiguity and imperfect signals. Partner with data science and research to understand how the system is performing and where to focus next. Collaborate across Hinge. Work with Growth, Trust & Safety, Marketing, and other teams to make sure recommendations feel integrated and aligned with the broader product experience. Champion fairness and integrity. Recommendations shape visibility and connection. Ensure the system reflects Hinge's values, avoids unintended bias, and supports an experience that feels safe and equitable for everyone. 6+ years of product management experience, ideally on personalization, recommendations, or other ML-powered consumer products Technical background or deep familiarity with the nuts and bolts of machine learning and AI A track record of building and improving consumer products at scale Experience partnering with engineering, data science, and research Strong communication skills, especially when translating complex ideas to non-technical audiences Comfort with ambiguity and making principled calls in high-impact spaces Curiosity about dating and the human side of product development An interest in the fairness, ethics, and inclusivity of algorithmic systems", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/29613669", "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": 1758171675, "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": 25426719, "name": "Backend Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1758171675, "t_create": 1728067142, "ats_job_id": "8e6e2a42-65f8-4bbf-82c4-13e78486a75e", "display_job_id": "8e6e2a42-65f8-4bbf-82c4-13e78486a75e", "type": "ATS", "id_locale": "1237468416418139759-en", "job_description": "Design and build Web APIs for a microservice architecture. Build out features for an internal React-based web application used for Moderation. Taking part in the backend On-Call rotation (around a week per quarter) Design and develop distributed systems in Go using cloud infrastructure, ensuring high performance and scalability. Lead projects end-to-end from technical design to implementation, while managing personal workload, meetings and timelines effectively. Collaborate across teams, promoting a culture of inclusivity, growth, and strong cross-functional communication. 3+ years of industry experience as a backend/service engineer 1+ year experience with building and maintaining React web applications (Javascript, Typescript, CSS) 2+ years of experience working in a cloud environment such as GCP, AWS, Azure. Strong programming skills: Familiarity with Go is a bonus! System Design & Architecture: Familiarity with distributed computing concepts Collaboration and Communication skills: Ability to clearly communicate complex ideas to teammates. 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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). 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