Machine Learning Engineer II Hot Job Los Angeles, California Department Engineering

As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing.

We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more.

The Tinder ML team drives impact across nearly every core domain of the product — Recommendations, Trust & Safety, Profile, Chat, Growth, and Revenue optimization. Our mission is to apply machine learning to enhance user experiences, foster trust, and accelerate business growth across Tinder’s ecosystem.

ML at Tinder is organized into three groups with distinct roles:

Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training, serving, and feature management

Machine Learning Software Engineers who bridge the gap between research and production by delivering machine learning models into real-world product experiences at scale

We are looking for a Machine Learning Engineer II to help build and ship machine learning systems that improve product experience and drive measurable business impact. This role is ideal for an engineer with a strong foundation in machine learning and software engineering who is excited to work on real-world problems, partner cross-functionally, and grow quickly in a high-impact environment.

This is an individual contributor role focused on modeling and algorithmic innovation. You will work closely with product, engineering, data, and platform partners to translate product opportunities into machine learning solutions, run experiments, and help bring models from development into production. The team’s work directly translates into measurable business outcomes, and many of its models are embedded in core Tinder user flows at scale.

This is a hybrid role and requires in-office collaboration three times per week in Palo Alto, California.

• Translate product and business problems into clear machine learning problems with measurable success criteria
• Build, train, evaluate, and improve production machine learning models
• Partner with software engineers and ML infrastructure engineers to deploy models and improve reliability, scalability, and performance in production
• Design and analyze offline evaluations and online experiments to understand model impact
• Contribute to feature engineering, data preparation, training pipelines, and model monitoring
• Write clean, maintainable, production-quality code and participate in design and code reviews
• Communicate technical findings, trade-offs, and recommendations clearly to both technical and non-technical partners

• BS or MS in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field
• 1+ year of industry experience in machine learning, software engineering, data science, or a related field
• Strong foundation in computer science fundamentals, including data structures, algorithms, and software design
• Experience building ML or AI-related systems, or strong understanding of how modern machine learning systems are developed and operated
• Proficiency in Python and at least one additional programming language such as Java, Kotlin, Go, Scala, or a similar language
• Strong understanding of machine learning fundamentals, including model training, evaluation, and experimentation
• Strong communication skills and the ability to collaborate effectively across functions
• Self-motivated, proactive, and comfortable taking ownership of well-scoped problems

• Experience with recommendation systems or casual inference
• Familiarity with big data or stream processing frameworks such as Spark or Flink
• Familiarity with cloud platforms…