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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 that provides clean, accurate, and robust data sets to 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. Contribute meaningful insights and feedback to our team processes. Participate in our on-call rotation. Perform other job-related duties as assigned. Proficient in Python, SQL, DevOps, and databases. 3+ years of professional/industry experience. Experience delivering data products from conception to delivery and with the infrastructure that supports their underlying processes. Strong communication skills (written/verbal).Experience modeling data sets for different types of sources and business processes. Passionate about designing elegant data infrastructure, tooling, and pipelines. Familiar with our stack: Kubernetes, Docker, Terraform, Kafka, Airflow, dbt, Looker, AWS technologies (S3, Redshift), GCP technologies (Dataflow, BigQuery), and CI/CD technologies (CircleCI).", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/19894338", "isPrivate": false}, {"id": 19938972, "name": "Senior ML Platform Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1734757283, "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": 25379117, "name": "Lead UX Researcher, Monetization", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Product", "t_update": 1734757283, "t_create": 1727813883, "ats_job_id": "577ea31f-dc6a-4145-bca6-9776c7426f4d", "display_job_id": "577ea31f-dc6a-4145-bca6-9776c7426f4d", "type": "ATS", "id_locale": "681196102899533002-en", "job_description": "Co-create monetization roadmap and strategy: Own and develop research suite on revenue opportunities for various audiences, in close partnership with cross-functional team. Develop and execute end-to-end research: Conduct end-to-end research using appropriate methods that range from strategic to iterative and evaluative to help team achieve goals. Cross-functional partner: Work in close collaboration with other researchers, product team members (i.e., product managers and designers) and cross-functional partners (i.e., data science, customer experience, marketing and brand strategy) to identify key research questions and prioritize projects in the short and long term. Insights-driven storytelling: Generate actionable insights and communicate them in compelling and creative ways; bridge alignment across Hinge teams through written reports and live presentations to cross-functional partners. Culture champion: Engage in and inspire honest and clear communication, promoting a culture of care, empathy, and respect. 6+ years of user research experience, including 2-3 years of experience in a consumer-facing product research role. Experience working on monetization, subscriptions or new revenue streams or zero-to-one products. Possess strong quantitative (e.g., survey, experimental) skills and expertise with measuring sentiment in experiment frameworks. Strong communicator, committed to telling clear and compelling stories with data. Proficient in data manipulation, analysis, and dashboard creation with R, SPSS, and/or Looker (or similar statistical software.) Proactive at building and sustaining trusting, successful relationships with cross-functional partners (e.g. data science, customer experience, product management, design, engineering, marketing.) Eager to learn from, collaborate with, and mentor other researchers.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "hybrid", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/25379117", "isPrivate": false}, {"id": 25720841, "name": "Senior Data Engineer, Product Platform", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1734757283, "t_create": 1729281095, "ats_job_id": "0164e706-70ce-49c2-8332-83d7eb4ce607", "display_job_id": "0164e706-70ce-49c2-8332-83d7eb4ce607", "type": "ATS", "id_locale": "6219524504621370144-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": 19920639, "name": "Senior ML Engineer, Growth", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1734757283, "t_create": 1704920293, "ats_job_id": "cc9bba44-65fd-43c4-bb19-2dd9a34f62c4", "display_job_id": "cc9bba44-65fd-43c4-bb19-2dd9a34f62c4", "type": "ATS", "id_locale": "6438892658509713149-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": 23551272, "name": "Senior Platform Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1734757283, "t_create": 1718726191, "ats_job_id": "dad03272-1785-4283-ae68-f1cbae4d12d4", "display_job_id": "R0003944", "type": "ATS", "id_locale": "R0003944-en", "job_description": "Deliver improvements to our infrastructure, observability, security, and internal tooling across varying problem spaces. Design, build, and maintain global, highly available, low-latency infrastructure to service the needs of our customers. Partner internally with teams to improve performance, scalability, reliability and observability of our infrastructure. Empathetically help teams improve their systems' performance, scalability, reliability, and observability. Has a keen focus on performance and reliability of infrastructure and takes ownership of solving problems as they arise. Leave a trail of high-quality technical documentation of initiatives, postmortems, and endeavor to uphold good knowledge-sharing practices. Impart your domain expertise theoretically and practically. Join the Platform Engineering on-call rotation. Prior experience in implementing, configuring and optimizing Kubernetes and Terraform at scale. Experience in building and troubleshooting large-scale distributed production infrastructure in AWS or GCP. Demonstrated proficiency in working on CI/CD pipelines. Experience building global multi-region infrastructure, services, databases and storage. Experience in on call rotation and responding to incidents. Proficiency working in Go or similar systems programming language. Has expertise in many or all of the following: Terraform, Kubernetes, AWS, Grafana, Elasticsearch, Prometheus, Argo CD,and Kafka", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/23551272", "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": 1734757283, "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. 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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. 5+ years of industry experience as a backend/service engineer 4+ years of experience working in a cloud environment such as GCP, AWS, Azure. Strong programming skills: Proficiency with Go and Python is a bonus! System design & architecture: A deep understanding of distributed computing concepts, event based architecture, and cloud design patterns. Collaboration and communication skills: Solid writing skills paired with the ability to clearly communicate complex ideas to teammates from both technical and non-technical backgrounds. 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