hinge jobs in Match Group

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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). 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": 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": 1750654908, "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": 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": 1750654908, "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": 29782276, "name": "PR Manager", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Marketing", "t_update": 1750654908, "t_create": 1750443396, "ats_job_id": "90e9f704-42d2-4b5f-a600-bc180f820df9", "display_job_id": "90e9f704-42d2-4b5f-a600-bc180f820df9", "type": "ATS", "id_locale": "3917452463556182009-en", "job_description": "Communication Plans: Implement PR strategies for company announcements. Support Story Development: Contribute to shaping story ideas across a variety of dating-forward and corporate PR storytelling activities. Collaborate Cross-Functionally: Coordinate with team members, PR agencies, subject matter experts, and research partners to gather insights and support campaign rollout and media requests. Execute Media Outreach: Pitch and place stories with lifestyle, tech, and business press \u2014 developing relationships with relevant reporters, editors and influential voices quoted in press. Assist Executive Comms: Help craft talking points, interview prep materials, and early-stage narratives for executives and subject matter experts. Organize Executive Visibility: Maintain and regularly update a shared view of executive comms activity - including speaking moments, milestones, and media opportunities - to support team awareness and planning. Write with Clarity: Draft press materials, talking points, and newsroom content in partnership with senior team members that reflect Hinge's tone and connect with our target audiences. Support Team Operations: Help maintain team tools, calendars, and process documentation in support of our communications function running smoothly and efficiently. Track Culture & Trends: Monitor news cycles and identify timely hooks for reactive and proactive pitching. Manage Press Inquiries: Respond to inbound requests from journalists. 4+ Years Experience: Ideally in public relations, communications, or journalism, with at least some experience in a fast-paced or consumer-facing organization. Curious About Emerging Tech: Proactive about learning about new technologies like AI and have an understanding about how they can shape consumer behavior with brands, platforms, and each other. We recognize that we are each always learning and adapting too. Strong Editorial Instincts: You know a good story when you see one and how to frame it for a reporter. Journalism experience is a plus. Media Relations Experience: Demonstrated success pitching media and landing earned coverage across lifestyle, business, and/or tech. Clear, Concise Writing: Exceptional written communication and an ability to adapt your tone to fit different formats. Culturally Engaged: Interested in dating, relationships, internet culture, and the conversations shaping how people connect. Team-Oriented: Collaborative, flexible, and comfortable working with multiple stakeholders to achieve the best outcome. Research-Minded: You ask thoughtful questions and enjoy digging into data or trends to find story potential. Organized & Detail-Oriented: Strong follow-through on tasks big and small. Initiative & Adaptability: You're confident prioritizing your work, troubleshooting issues as they arise, knowing when to escalate or ask for input, and staying flexible as priorities shift. Values-Aligned: You're excited to support a mission that centers on connection, empathy, and authenticity, and help others see that in our stories.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/29782276", "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": 1750654908, "t_create": 1749676109, "ats_job_id": "da192775-c278-4906-8776-204d7032c291", "display_job_id": "da192775-c278-4906-8776-204d7032c291", "type": "ATS", "id_locale": "3597404255467662710-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": 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": 1750654908, "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": 25720841, "name": "Senior Data Engineer, Trust & Safety", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1750654908, "t_create": 1729281095, "ats_job_id": "0164e706-70ce-49c2-8332-83d7eb4ce607", "display_job_id": "R0004272", "type": "ATS", "id_locale": "R0004272-en", "job_description": "Work with our data teams to ensure data is flowing accurately through data creation to our presentation layers. Improve our Data Engineering stack through containerization, data modeling, developing our ETL pipelines, and more. 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. Passionate about designing elegant data infrastructure, tooling, and pipelines. Familiarity with our stack: Kubernetes, Docker, Terraform, Kafka, Airflow, dbt, Looker, AWS technologies (S3, Redshift), GCP technologies (Dataflow, BigQuery). and CI/CD technologies (CircleCI). 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Swift Proficiency: Develop and continuously enhance your understanding of Swift fundamentals, applying them to create efficient and effective solutions. iOS Expertise: Gain a thorough understanding of iOS development principles, Apple's Human Interface Guidelines, and architectural design patterns, applying them to build intuitive and user-friendly applications. Issue Resolution: Triage, debug, and effectively resolve software issues, ensuring the stability and performance of our application. Codebase Stewardship: Actively contribute to the long-term health and evolution of the codebase, implementing best practices and innovative solutions. Code Reviews: Regularly perform code reviews, providing constructive feedback to peers to foster a culture of excellence and continuous improvement. Active Team Participation: Engage actively in team ceremonies such as stand-ups, planning sessions, and retrospectives to ensure alignment and promote agile methodologies. Effective Communication: Maintain clear and positive communication with team members and other departments, supporting an empowering and inclusive team environment. Professional iOS Development Experience: You have 3-5 FTE years of experience in iOS development, demonstrating the ability to design and implement mobile applications effectively. App Store Publication: You have experience publishing at least one application on the App Store, showcasing your understanding of the deployment process and maintaining a production application. Proficiency in Swift and iOS Frameworks: You are proficient in Swift and have a strong understanding of iOS SDKs and frameworks. Solid Software Development Fundamentals: You possess a good foundation in software development principles and are capable of creating efficient and maintainable code. Strong Communication Skills: You are able to communicate clearly and effectively, facilitating productive collaborations within technical and non-technical teams. Ownership and Quality Focus: You take pride in your work and are committed to creating high-quality user experiences, demonstrating attention to detail and a user-centric approach to application development. 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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.. 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