Match Group

Machine Learning Engineer

New York, New York, United States

Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
AI & Machine Learning, Consumer SoftwareIndustries

Job Description

Position Overview

  • Location Type: Remote
  • Employment Type: Full-time
  • Salary: Not specified

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. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. 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 making sure people get to see their most compatible matches as well as helping them better present themselves or even start a conversation when they match with someone. In short, we help people go on dates! 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. 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.

Requirements

  • 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, 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 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, and recommender systems are a plus.
  • Dev-ops skills: The ability to establish, manage, and use data and compute infrastructure such as Kubernetes and Terraform.
  • Data engineering knowledge: Understanding of data pipelines and processing.

Responsibilities

  • Own and contribute to foundational models (e.g., CLIP embeddings) that power our recommendations pipelines.
  • Contribute to the research and development of recommender models and 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 for doing ML at scale.
  • Perform other job-related duties as assigned.

Application Instructions

  • Not specified

Skills

Python
Java
C++
System Design
Machine Learning
DNNs
GCP
AWS
Azure
Ray
KubeFlow
W&B
Cloud Computing
Distributed Computing
Recommendation Systems
LLMs
Embedding Models
Predictive Models

Match Group

Provides online dating and social discovery

About Match Group

Match Group leverages the Swipe feature® and social discovery, facilitating deeper connections through its portfolio of online dating brands, with a global presence and availability in over 40 languages.

Dallas, TexasHeadquarters
1986Year Founded
$400MTotal Funding
IPOCompany Stage
Consumer Software, Social ImpactIndustries
1,001-5,000Employees

Benefits

Medical/Dental/Vision Insurance
Charitable Matching Program
Retirement Matching Funds
Training and Education Allowance
Performance Bonuses
Mental Health Counseling

Risks

Increased competition from AI-driven dating apps may draw users away.
Privacy concerns and data breaches could impact reputation and operations.
Free dating apps with innovative features may pressure Match Group's pricing models.

Differentiation

Match Group offers nearly 50 brands catering to diverse dating communities.
The company generates revenue through subscription, transaction, and advertising models.
Match Group operates globally, available in over 200 countries and 40 languages.

Upsides

Increased interest in AI-driven matchmaking enhances user experience and engagement.
Growing trend of VR integration offers immersive dating experiences.
Rising demand for niche platforms caters to specific interests and communities.

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