Machine Learning Engineer, Hinge
Trust & Safety
$150-198k
SQL
AWS
Kubernetes
GCP
Python
Azure
Spark
Kubeflow
PyTorch
Junior and Mid level
New York
Dating app for meaningful relationships
Be an early applicant
Dating app for meaningful relationships
201-500 employees
B2CLifestyleDating
Be an early applicant
$150-198k
SQL
AWS
Kubernetes
GCP
Python
Azure
Spark
Kubeflow
PyTorch
Junior and Mid level
New York
201-500 employees
B2CLifestyleDating
Company mission
To create a less lonely world by inspiring intimate, in-person connections.
Role
Who you are
- Strong programming skills: Proficiency in Python and SQL, comfort with at least one ML stack (e.g., PyTorch, Hugging Face Transformers), and a working understanding of data pipelines
- Domain expertise: Solid understanding of machine learning, deep learning, and emerging AI techniques. Track record of building, debugging, and fine-tuning ML models for user-facing products. Experience with content classification, fraud detection, or related Trust & Safety problems is a plus
- System design & architecture: Experience training and deploying ML models in production. Working understanding of distributed computing for inference and training
- AI application: Hands-on with AI agents, RAG, structured outputs, and function/tool calling. Understands when to reach for an agent or LLM vs. a classical ML approach
- Evaluation frameworks for ML and LLM systems: Comfort designing and running evaluations to measure model effectiveness, fairness, and safety across both classical ML and LLM systems. Familiar with golden datasets, LLM-as-judge patterns, precision/recall/F1, false positive rates, hallucination, and offline/online metrics
- Cloud and data platform proficiency: Hands-on with at least one cloud environment (GCP, AWS, or Azure). Familiarity with Databricks, Ray, or Kubeflow is a plus
- Data engineering knowledge: Comfortable handling large datasets, including cleaning, preprocessing, and storage, and contributing to batch and streaming pipelines orchestrated with tools like Databricks or Argo
- Project ownership: Demonstrated ability to drive medium-sized projects to completion, identify and unblock yourself on technical issues, and ship measurable outcomes with limited oversight
- 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
- 2+ years of experience as an MLE, applied scientist, or data scientist (depending on education)
- 1+ years of experience applying end-to-end machine learning models in an industry setting — including data collection, model training, deployment, and monitoring
- Experience integrating or evaluating LLMs in real-world applications with appropriate baseline metrics and evaluation methodologies is a plus
- Familiarity with at least one ML infrastructure component (feature store, training environment, model serving, observability, workflow orchestrator)
- Previous exposure to Trust & Safety, fraud detection, content classification, or compliance is preferred but not required
- Demonstrated use of modern AI tooling in their actual workflow (e.g., Cursor, Claude Code, Codex)
- A degree in computer science, engineering, or a related field (or equivalent practical experience)
What the job involves
- Join Hinge as a Machine Learning Engineer on the Trust & Safety team, where you'll apply AI and machine learning to mitigate the impact of policy violating actors, remove harmful content, and keep our users safe on the platform
- Working alongside an established Trust & Safety AI team, you'll partner with product managers, data scientists, engineers, and analysts to build, deploy, and improve detection systems that have a direct, measurable impact on user safety
- This is a high-ownership IC role on a small team with a large mission. You'll own the end-to-end lifecycle of ML projects, contribute to a growing portfolio of AI-powered safety features, and grow alongside senior engineers, all while playing a foundational role in how Hinge applies machine learning to give users a safer experience on their journey to find intimate connection
- Build, deploy, and maintain end-to-end machine learning models that detect policy violating actors, remove harmful content, and keep users safe
- Own medium-sized projects end-to-end (from problem scoping and data collection to training, deployment, monitoring, and iteration)
- Contribute to scalable inference and data pipelines (e.g., Spark, Kubernetes), including preprocessing, batch and real-time inference, and post-processing components
- Apply standardized performance metrics, testing protocols, and evaluation processes to measure model effectiveness and identify risks
- Continuously assess and refine deployed models using user feedback, business impact signals, and emerging policy and ethical considerations
- Collaborate closely with Data Scientists, Data Engineers, Product Managers, Backend Engineers, and the AI Platform team to ship coordinated user safety improvements
- Stay current on advances in AI/ML, particularly LLMs and evaluation methods, and apply appropriate techniques to detection and user safety problems
Our take
Hinge is a dating app that stands out by prioritizing meaningful relationships over casual hookups. Designed for people seeking long-term commitments, it moves away from the typical "swipe" approach popularized by apps like Tinder. Instead, Hinge emphasized detailed profiles and compatibility-based recommendations so used can make deeper, more genuine connections.
Back in 2019, half of single people in the US had never tried a dating app. Fast forward to today, and online dating is just part of the norm. Hinge has carved out its place in this market by focusing on long-term meaningful relationships, and is certainly meeting the growing demand for companionship while riding the wave of the online dating trend.
The "dating app designed to be deleted" is the fastest-growing dating app on the market and with online dating becoming the mainstream, Hinge looks pretty set to stay at the top.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Top investors
48% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Dec 2014
$12m
SERIES A
Jul 2014
$4.5m
CONVERTIBLE
Total funding: $20.6m
Company benefits
- Hybrid and Remote Work: If you're hybrid, you'll come in three times a week. We host our biweekly All-Hands meetings on Wednesdays (often with sweet treats).
- Dating: Experience what our users experience. All US-based Hinge employees receive a $100 monthly stipend for epic dates. Hinge Premium is also free for all employees and their loved ones.
- Retirement Benefits: We match 100% of the first 10% of pre-tax 401(k) contributions you make, up to a maximum of $10,000 per year.
- Health Insurance: high-quality medical, dental, and vision coverage for you and your family.
- Paid Time Off: 20 accruable vacation days annually. Plus 1 floating holiday, 10 wellness days, 1 community service day, and a generous company holiday calendar. PTO increases with tenure after 2 years with the company.
- Parental Leave & Planning: When you become a new parent, you’re eligible for 100% paid parental leave (20 paid weeks for both birth and non-birth parents). We also subsidize fertility care and preservation services.
- Wellness: We subsidize OneMedical, ClassPass, and CitiBike memberships. You and your dependents also have access to individual therapy, group therapy, and coaching services through Modern Health.
- Professional Growth: receive a $3,000 annual Learning & Development stipend after three months, along with free access to Udemy, an online marketplace with over 6,000 courses, starting on your first day.
- Meals: Receive a $30 weekly Seamless credit. In the NYC office, we offer plenty of options for snacks and drinks. Plus, free catered lunches in the office Tuesday through Thursday. In-office lunch varies by location.
- Community Service: We match charitable donations dollar for dollar to a maximum of $15,000 per employee, and give every US-based employee 1 day off for community service annually.
- Commuting: Every US-based hybrid employee gets a $125 monthly commuter subsidy to use for public transportation, parking, bike maintenance and storage, and more.
- Pets: Feel free to bring your best friend to work with you to the NYC office. For US-based employees, we’ll provide pet insurance for your furry family members, too.
- Legal Coverage: You’ll receive low cost access to legal coverage that covers custody and support matters, divorce, real estate and home ownership, tenancy issues, tax issues, wills and estate planning, and more.
- Fertility Support: You’ll get easy access to fertility care through Carrot, from basic treatments to fertility preservation. We also provide $10,000 toward fertility preservation. You and your spouse/domestic partner are both eligible.
Company HQ
West Village, New York, NY
Leadership
Justin McLeod
(Founder & CEO)Having studied at Colgate University and Harvard Business School, Justin founded Hinge in February 2011. He has served as CEO since.
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