Machine Learning Engineer Job at Hinge in New York
Hinge, New York, NY, United States
Hinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. With tens of millions of users across the globe, we’ve become the most trusted way to find a relationship, for all.
About the Role The Dating Outcomes group is responsible for ensuring people see their most compatible matches, helping them better present themselves, and even starting a conversation when they match with someone. We are hiring ML practitioners to help us build the foundations of an AI first dating experience using the latest advancements in the field leveraging Hinge’s years worth of preference data. You can expect to work on recommendation systems end to end, experiment with using LLMs, photo and mixed input embedding models as well as building and deploying real time predictive models that directly impact millions of users’ experience.
Responsibilities Own and contribute to foundational models that power our recommendation pipelines.
Contribute to the research and development of recommender models and experiment with the latest ML innovations such as LLM agents and transcription models.
Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering incremental impact to our daters.
Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand needs and identify opportunities to accelerate the AI/ML development and deployment process.
Mentor and educate ML Engineers on current and up‑to‑date research, technologies, and best practices for ML at scale.
Perform other job‑related duties as assigned.
What We’re Looking For Strong programming skills : Proficiency in Python, Java, or C++.
System design & architecture : Proven track record of training and deploying large‑scale ML models, especially DNNs, and understanding of distributed computing for learning and inference.
Cloud platform proficiency : Ability to utilize cloud environments such as GCP, AWS, or Azure; familiarity with ML serving solutions is a plus.
ML knowledge : Deep understanding of DNN architectures, debugging, and fine‑tuning models; experience with recommender systems is a plus.
Dev‑ops skills : Experience managing data and compute infrastructure such as Kubernetes and Terraform.
Data engineering knowledge : Skills in handling and managing large datasets, batch and streaming pipelines, and orchestrators.
Collaboration and communication skills : Ability to work effectively in a team and communicate complex ideas clearly.
Strong written communication : Ability to document and communicate technical knowledge clearly.
Software leadership skills : Track record of leading projects through completion with quantifiable outcomes.
3+ years of experience as an MLE.
2+ years of experience with cloud environments and dev‑ops tooling.
1+ year of experience leading projects with at least one other team member.
2+ years of experience designing and developing online and production‑grade ML systems.
A degree in computer science, engineering, or a related field.
Salary Range $162,000.00 – $210,000.00 per year salary.
Equal Opportunity Employer Hinge is an equal opportunity employer. We value diversity and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds.
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In Summary: Dating Outcomes group responsible for ensuring people see their most compatible matches, helping them better present themselves, and even starting a conversation when they match . Hinge is hiring ML practitioners to help us build the foundations of an AI first dating experience using the latest advancements in the field .
En Español: En Hinge, estamos en una misión de inspirar conexiones íntimas para crear un mundo menos solitario. Con decenas de millones de usuarios en todo el mundo, nos hemos convertido en la forma más confiable de encontrar una relación, para todos. Puede esperar trabajar en sistemas de recomendación de extremo a extremo, experimentar con el uso de LLM, modelos de incorporación de entradas fotográficas y mixtas, así como la creación e implementación de modelos predictivos en tiempo real que impacten directamente en la experiencia de millones de usuarios. Responsabilidades Propiedad y contribución a los modelos fundamentales que impulsan nuestras tuberías de recomendaciones. Contribuir a la investigación y desarrollo de modelos recomendadores y experimentación con las últimas innovaciones ML tales como agentes LLM y modelos de transcripción. Diseñar, abogar e implementar para la disponibilidad, escalabilidad, excelencia operativa y gestión de costes al mismo tiempo que brinda un impacto incremental a nuestros daters. Colaborar estrechamente con ingenieros de datos, científicos de datos y gerentes de productos para comprender mejor las necesidades y oportunidades para acelerar el desarrollo y despliegue del proceso de computación/ML AWS: Mentor y asesores de trabajo: : A.: Desarrollar claramente conocimientos avanzados sobre las habilidades de aprendizaje en línea y desarrollando nuevas tecnologías de comunicación, Protecnología de información y procesamiento de datos. Valoramos la diversidad y no discriminamos en base a raza, religión, color, origen nacional, género, orientación sexual, edad, estado civil, estatus de veterano o condición de discapacidad. Creemos que el éxito se crea por una fuerza laboral diversa de individuos con diferentes ideas, fortalezas, intereses y antecedentes culturales. #J-18808-Ljbffr
About the Role The Dating Outcomes group is responsible for ensuring people see their most compatible matches, helping them better present themselves, and even starting a conversation when they match with someone. We are hiring ML practitioners to help us build the foundations of an AI first dating experience using the latest advancements in the field leveraging Hinge’s years worth of preference data. You can expect to work on recommendation systems end to end, experiment with using LLMs, photo and mixed input embedding models as well as building and deploying real time predictive models that directly impact millions of users’ experience.
Responsibilities Own and contribute to foundational models that power our recommendation pipelines.
Contribute to the research and development of recommender models and experiment with the latest ML innovations such as LLM agents and transcription models.
Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering incremental impact to our daters.
Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand needs and identify opportunities to accelerate the AI/ML development and deployment process.
Mentor and educate ML Engineers on current and up‑to‑date research, technologies, and best practices for ML at scale.
Perform other job‑related duties as assigned.
What We’re Looking For Strong programming skills : Proficiency in Python, Java, or C++.
System design & architecture : Proven track record of training and deploying large‑scale ML models, especially DNNs, and understanding of distributed computing for learning and inference.
Cloud platform proficiency : Ability to utilize cloud environments such as GCP, AWS, or Azure; familiarity with ML serving solutions is a plus.
ML knowledge : Deep understanding of DNN architectures, debugging, and fine‑tuning models; experience with recommender systems is a plus.
Dev‑ops skills : Experience managing data and compute infrastructure such as Kubernetes and Terraform.
Data engineering knowledge : Skills in handling and managing large datasets, batch and streaming pipelines, and orchestrators.
Collaboration and communication skills : Ability to work effectively in a team and communicate complex ideas clearly.
Strong written communication : Ability to document and communicate technical knowledge clearly.
Software leadership skills : Track record of leading projects through completion with quantifiable outcomes.
3+ years of experience as an MLE.
2+ years of experience with cloud environments and dev‑ops tooling.
1+ year of experience leading projects with at least one other team member.
2+ years of experience designing and developing online and production‑grade ML systems.
A degree in computer science, engineering, or a related field.
Salary Range $162,000.00 – $210,000.00 per year salary.
Equal Opportunity Employer Hinge is an equal opportunity employer. We value diversity and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds.
#J-18808-Ljbffr
In Summary: Dating Outcomes group responsible for ensuring people see their most compatible matches, helping them better present themselves, and even starting a conversation when they match . Hinge is hiring ML practitioners to help us build the foundations of an AI first dating experience using the latest advancements in the field .
En Español: En Hinge, estamos en una misión de inspirar conexiones íntimas para crear un mundo menos solitario. Con decenas de millones de usuarios en todo el mundo, nos hemos convertido en la forma más confiable de encontrar una relación, para todos. Puede esperar trabajar en sistemas de recomendación de extremo a extremo, experimentar con el uso de LLM, modelos de incorporación de entradas fotográficas y mixtas, así como la creación e implementación de modelos predictivos en tiempo real que impacten directamente en la experiencia de millones de usuarios. Responsabilidades Propiedad y contribución a los modelos fundamentales que impulsan nuestras tuberías de recomendaciones. Contribuir a la investigación y desarrollo de modelos recomendadores y experimentación con las últimas innovaciones ML tales como agentes LLM y modelos de transcripción. Diseñar, abogar e implementar para la disponibilidad, escalabilidad, excelencia operativa y gestión de costes al mismo tiempo que brinda un impacto incremental a nuestros daters. Colaborar estrechamente con ingenieros de datos, científicos de datos y gerentes de productos para comprender mejor las necesidades y oportunidades para acelerar el desarrollo y despliegue del proceso de computación/ML AWS: Mentor y asesores de trabajo: : A.: Desarrollar claramente conocimientos avanzados sobre las habilidades de aprendizaje en línea y desarrollando nuevas tecnologías de comunicación, Protecnología de información y procesamiento de datos. Valoramos la diversidad y no discriminamos en base a raza, religión, color, origen nacional, género, orientación sexual, edad, estado civil, estatus de veterano o condición de discapacidad. Creemos que el éxito se crea por una fuerza laboral diversa de individuos con diferentes ideas, fortalezas, intereses y antecedentes culturales. #J-18808-Ljbffr