Machine Learning Engineer, Hinge

$177-213k

AWS
Kubernetes
GCP
Python
Java
Airflow
Terraform
C++
Azure
Kubeflow
PyTorch
Mid and Senior level
New York
Hinge

Dating app for meaningful relationships

Open for applications

Hinge

Dating app for meaningful relationships

201-500 employees

B2CLifestyleDating

Open for applications

$177-213k

AWS
Kubernetes
GCP
Python
Java
Airflow
Terraform
C++
Azure
Kubeflow
PyTorch
Mid and Senior level
New York

201-500 employees

B2CLifestyleDating

Company mission

To help singles build meaningful relationships by connecting in person, helping people to get off dating apps.

Role

Who you are

  • 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

What the job involves

  • We are hiring senior/staff 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
  • This is a fast-growing team and you will get a chance to own and define the strategy, vision, and plan for how to accelerate machine learning at Hinge
  • 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

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Insights

Top investors

48% employee growth in 12 months

Company

Company benefits

  • Equal opportunity employer
  • 401k plan
  • Accrual time off model
  • Stocked kitchen
  • Monthly date stipend
  • Pet friendly
  • Work from home opportunities
  • Health insurance

Funding (last 2 of 4 rounds)

Dec 2014

$12m

SERIES A

Jul 2014

$4.5m

CONVERTIBLE

Total funding: $20.6m

Our take

Hinge is a dating app that sets itself apart from its competitors by focusing on relationships over hookups. It predominantly caters to people looking for long-term commitments. It has abandoned the “swipe” approach that’s often associated with game-like dating apps, such as Tinder, and instead it focuses on in-depth profiles and compatibility recommendations to help users better connect with each other.

In 2019, 50% of single people in the US had never used a dating app. Now, online dating has become part of the new normal, and Hinge’s focus on long-term, meaningful relationships is well-positioned to tap into the current desire for companionship and stability, as well as the growing market trend toward online dating.

The "dating app designed to be deleted" is the fastest-growing dating app on the market and is seeing further success following new capability expansions and acquisition by dating app portfolio Match Group in 2019. All this being said, there is growing concern over fake accounts and fraudulent activity on Hinge, as there is with other competing dating apps. Pricing tiers and more robust regulations for profiles are currently combatting this.

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Freddie

Company Specialist at Welcome to the Jungle