Match Group jobs in new york new york

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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": 20079076, "name": "Machine Learning Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1743570096, "t_create": 1705101155, "ats_job_id": "3fc3a7d4-4a84-4eb9-80d6-ab3c549c6171", "display_job_id": "R0004232", "type": "ATS", "id_locale": "R0004232-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": 25426719, "name": "Backend Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1743570096, "t_create": 1728067142, "ats_job_id": "8e6e2a42-65f8-4bbf-82c4-13e78486a75e", "display_job_id": "R0003965", "type": "ATS", "id_locale": "R0003965-en", "job_description": "Design and build RESTful APIs for mobile clients. Taking part in the backend On-Call rotation (1 whole week, every 8-11 weeks). Design and build microservices that run on Kubernetes. Design and build distributed systems in Go, using cloud infrastructure and platform service components. Own the technical design, implementation, and success of their projects. Collaborate effectively with cross-functional partners. Help foster a culture of collaboration and inclusivity. Cultivate a growth mindset. Effectively organize and manage personal workload, tasks, and meetings. 3+ years of industry experience as a backend/service engineer. 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. Cloud Technologies: Familiarity with Kubernetes, OpenTelemetry, gRPC/Protobuf, etc.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/25426719", "isPrivate": false}, {"id": 25720841, "name": "Senior Data Engineer, Dating Outcomes", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1743570096, "t_create": 1729281095, "ats_job_id": "0164e706-70ce-49c2-8332-83d7eb4ce607", "display_job_id": "R0004222", "type": "ATS", "id_locale": "R0004222-en", "job_description": "Design, build, and optimize data pipelines that support critical foundational, cross-cutting product services, empowering the product team to make informed decisions. Drive advancements in our Data Engineering stack by implementing containerization, refining data modeling techniques, and evolving ETL pipeline development to support emerging business needs and scalability requirements. Leverage your data modeling expertise to design, build, and maintain our analytics data warehouse that delivers reliable, high-quality datasets for reporting, analytics, and machine learning purposes, supporting both short-term insights and long-term strategic initiatives. Advocate for Data Engineering best practices within the team, championing their adoption and supporting the continuous improvement of the team's capabilities. Work with stakeholders across the organization to understand their data needs and translate these needs into actionable data solutions. 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 in data engineering, delivering data products from conception to delivery and supporting their underlying infrastructure. Strong technical background in building and optimizing data pipelines, with proficiency in Python, SQL, and data modeling for different types of data sources and business processes. Technical expertise in the following: Python, Go, Kubernetes, Docker, Terraform, CircleCI, GitHub Actions, Kafka, PubSub, Dataflow, Redshift, BigQuery, Databricks, dbt, Looker Experience with cloud environments such as GCP, AWS, or Azure Strong communication skills (written and verbal), with an ability to work collaboratively with cross-functional teams, including backend engineering, data science, and product teams. Effective analytical, troubleshooting, and problem-solving skills, ensuring data systems operate efficiently and meet business needs. Mentorship experience, with a focus on guiding junior data engineers and contributing to team growth through knowledge-sharing and code reviews. 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/25720841", "isPrivate": false}, {"id": 26915420, "name": "Lead Product Manager, Monetization", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1743570096, "t_create": 1737134896, "ats_job_id": "5e7a1ddd-2999-4f7d-9091-b5149db40bd0", "display_job_id": "R0004168", "type": "ATS", "id_locale": "R0004168-en", "job_description": "Product Leadership: In this role you will be a leader within Growth, expected to work at the highest levels of the company to gain executive buy-in and sponsorship of your roadmap and project proposals. This role also involves close collaboration with our Finance leadership to meet Hinge's financial goals for the year. Product Strategy: Define and iterate Hinge's end-to-end strategy for monetizing our product, while maintaining a first-class experience for free users and aligning it with the company's overall goals and objectives. Experiment with pricing models, feature bundles and subscription tiers to enhance customer adoption and maximize revenue. Roadmap Planning: Create and maintain a clear product roadmap, regularly aligning with stakeholders. Communication: Clearly communicate roadmaps, priorities, experiments and decisions across the organization, from partner teams to executives. Feature Development: Lead and collaborate cross functionally on the ideation, design, technical development and launch of optimizations and new capabilities that will help users date more efficiently while helping Hinge drive exceed revenue goals. Data Analysis: Partner with data and analytics to track feature performance and make data-driven decisions to iterate. Analyze user behavior, engagement trends and revenue metrics to identify new growth and merchandising opportunities. Cross-functional Collaboration: Work closely with Hinge's other product, design, data, research, and engineering teams to ensure alignment, and effective execution. 6+ years product management experience, preferably with a background supporting consumer technology, marketplace platforms or subscription based products. Solid business acumen and comfort working closely with finance partners to define, track and deliver impactful outcomes. Proven track record of driving revenue growth through innovative product strategies and experiments. Deep understanding of pricing models, customer segmentation and subscription products. Strong analytics skills, with experience working with data tools Exceptional communication and storytelling abilities to influence stakeholders at all levels. Experience working with A/B testing frameworks and growth experimentation methodologies. A customer-centric mindset with a focus on delivering long term value.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/26915420", "isPrivate": false}, {"id": 27151514, "name": "Executive Assistant", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Operations", "t_update": 1743570096, "t_create": 1738598054, "ats_job_id": "a79f1a0b-b22f-402d-89af-a57085dda3cd", "display_job_id": "a79f1a0b-b22f-402d-89af-a57085dda3cd", "type": "ATS", "id_locale": "2896013653866514084-en", "job_description": "Bookings: Assist with professional event planning and provide on-site support as needed. Time Management: Ensure calendar aligns with priorities. Manage all work schedules, scheduling meetings and proactively identifying conflicts. Manage and prioritize to-do list. Meeting Preparation: Ensure CEO is prepared for all meetings - double checking calendar invites, confirming with outside guests, providing print-outs, greeting guests, etc. Email Inbox: Monitor and manage emails. Categorize, forward, archive and respond as appropriate. Errands and Tasks: Ensure routine items are stocked in the office. Run errands, perform administrative tasks, meet vendors, etc. Work Expenses: Handle expense reporting and reimbursement, meticulously tracking and reconciling expenses in compliance with company policy. When there is bandwidth or CEO support is minimal (which may happen depending on the week) this individual will also intermittently offer support to other Executive team members with work expenses, event bookings or light errands and tasks. Creative problem solver: You always find a way to get things done, even against the odds. You love to come up with creative solutions to hard problems, and you have a natural knack for creating \u201csurprise and delight\u201d moments. Critical, detail-oriented thinker: You know that details make the difference. You're a perceptive, active listener. You ask lots of questions and crave lots of context, always considering the \u201cwhy\u201d behind the \u201cwhat.\u201d Highly routinized and methodical: You insist on structure, and you gravitate toward setting up systems, processes and templates. Proactive: You see around corners to anticipate issues. You can always find something productive to do, even when not inundated with inbound requests. Positive, buoyant energy: You bring lots of energy to your interactions with others. You are extroverted, kind, and solutions-oriented. Strong communicator: You are a clear verbal and written communicator who can distill complex information into succinct summaries. You can read between the lines when interacting with others, and you know how to tailor your approach based on your audience. Integrity: You are honest, authentic, and keep all personal or confidential information strictly to yourself.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/27151514", "isPrivate": false}, {"id": 27213789, "name": "Scaled Operations Program Manager / Quality Operations Program (Trust and Safety)", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Trust & Safety", "t_update": 1743570096, "t_create": 1738966849, "ats_job_id": "07e5796e-4f35-4a6e-939c-015af822c317", "display_job_id": "07e5796e-4f35-4a6e-939c-015af822c317", "type": "ATS", "id_locale": "7312755052301178195-en", "job_description": "Quality Assurance Strategy & Execution: Develop and implement scalable QA frameworks, methodologies, and processes to ensure the accuracy, fairness, and efficiency of moderation decisions. Performance Monitoring & Insights: Establish key performance indicators (KPIs) and quality metrics to measure agent performance, decision accuracy, and process effectiveness. Process Optimization: Identify gaps in moderation workflows and recommend continuous improvement initiatives through automation, training enhancements, and best practice adoption. Training & Calibration: Partner with policy, training, and operations teams to create robust calibration processes, ensuring alignment between human moderators, AI models, and policy guidelines. Incident Management & Root Cause Analysis: Investigate quality-related issues, conduct root cause analysis, and implement corrective actions to mitigate risks and prevent recurrence. Data-Driven Decision Making: Analyze QA data and generate actionable insights to improve moderation outcomes, agent performance, and overall operational efficiency. Cross-functional Collaboration: Work closely with internal teams (Policy, Legal, Product, Engineering, and Operations) to align QA initiatives with business goals and regulatory requirements. Vendor & Partner Management: Oversee external QA vendors, ensuring adherence to quality standards and driving continuous process enhancements. Experience: 3+ years in quality assurance, content moderation, trust & safety operations, or a related field, preferably within a scaled operations environment. Industry Knowledge: Deep understanding of Trust & Safety, content moderation, and risk management processes, including regulatory compliance requirements. Analytical & Problem-Solving Skills: Strong data analysis capabilities, with experience leveraging QA tools, dashboards, and statistical insights to drive decision-making. Process Improvement Expertise: Proven ability to design, implement, and optimize QA frameworks and moderation workflows in high-volume operational settings. Collaboration & Leadership: Demonstrated ability to work cross-functionally, influence stakeholders, and drive alignment across global teams. Technical Skills: Familiarity with AI-driven moderation tools, quality monitoring platforms, and workflow automation solutions. Communication Skills: Excellent written and verbal communication skills, with the ability to convey complex concepts to both technical and non-technical audiences. 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Design and implement scalable systems (e.g., using Spark, Kubernetes) to preprocess data, run inference, and manage post-processing pipelines. Define standardized performance metrics, testing protocols, and evaluation processes to measure the effectiveness, identify and mitigate potential risks, and ensure fairness of AI solutions. Ensure ongoing assessment and refinement of AI solutions, incorporating user feedback, business impact, and emerging ethical considerations. Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform Team to ensure a comprehensive and coordinated approach to user safety. Stay abreast of new trends and research in AI/ML that can be applied to Trust & Safety initiatives to improve detection, user safety, and stay ahead of potential threats. Strong programming skills: Proficiency in languages like Python, Java or C++ and SQL, proficiency in at least one ML stack (e.g., PyTorch), and strong understanding of data pipelines Domain expertise: Deep understanding of machine learning, deep learning, and emerging AI technologies. Proven track record of building, debugging, and fine-tuning real-time machine learning models for user facing products. Experience with applying expertise to fraud detection, content moderation, or related fields is a plus . System design & architecture: Experience training and deploying large scale ML models. Good understanding of distributed computing for learning and inference. Evaluation frameworks for LLMs: Experience designing robust testing protocols to ensure effectiveness, fairness, and safety of AI-driven features. Cloud and data platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with solutions like Databricks, Ray, or KubeFlow 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. Strategic technical leadership skills: Demonstrated track record of guiding teams through complex ML projects in alignment with product and business objectives. 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. 4+ years of experience, depending on education, as an MLE or data scientist. 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Kotlin Proficiency: Develop and continuously enhance your understanding of Kotlin fundamentals, applying them to create efficient and effective solutions. Android Expertise: Gain a thorough understanding of Android development principles and 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. 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