Machine Learning Engineer II

Role overview

Tinder is focused on preserving the excitement of meeting new people at massive scale. The product serves tens of millions of users across 190+ countries, with hundreds of millions of downloads, more than 2 billion swipes each day, and over 20 million matches daily. The company applies machine learning, behavioral science, network economics, AI, and other disciplines to improve connections, safety, and user experiences.

Team context

The Machine Learning team contributes to major areas of the product, including recommendations, trust and safety, profile, chat, growth, and revenue optimization. The organization is split into three ML tracks: machine learning engineers who focus on modeling and algorithmic innovation, infrastructure engineers who build scalable tooling for training and serving, and software engineers who bring ML research into production product experiences.

What this role will do

This position is an individual contributor role centered on building and shipping machine learning systems that improve the product and create measurable business value. You will work across product, engineering, data, and platform teams to turn business needs into ML solutions, run experiments, and move models from development to production.

• Turn product and business needs into machine learning problems with clear success metrics
• Develop, train, assess, and refine ML models used in production
• Work with software and ML infrastructure partners to deploy models and improve reliability, scale, and performance
• Plan and interpret offline evaluations as well as online experiments to measure impact
• Support feature engineering, data preparation, training workflows, and model monitoring
• Produce clean, maintainable, production-ready code and take part in design and code reviews
• Present technical insights, trade-offs, and recommendations to technical and non-technical stakeholders

Work location and schedule

This is a hybrid position based in Palo Alto, California, with in-office collaboration required three days per week.

Required background

The ideal candidate has a strong grounding in machine learning and software engineering, along with the ability to work independently in a high-impact environment.

• BS or MS in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical discipline
• At least 1 year of industry experience in machine learning, software engineering, data science, or a related area
• Solid computer science fundamentals, including data structures, algorithms, and software design
• Experience building ML or AI systems, or strong understanding of how modern ML systems are developed and operated
• Strong Python skills plus proficiency in one additional language such as Java, Kotlin, Go, Scala, or similar
• Good grasp of ML basics, including training, evaluation, and experimentation
• Strong communication skills and the ability to collaborate across teams
• Self-driven and comfortable owning well-defined problems end to end

Preferred experience

• Work with recommendation systems or causal inference
• Exposure to big data or stream processing tools such as Spark or Flink
• Experience with cloud services like AWS and container platforms like Kubernetes
• Familiarity with ML serving systems such as TensorFlow Serving, TorchServe, Triton Inference Server, or Ray Serve
• Experience with feature stores, ML data pipelines, and orchestration tools such as Airflow
• Knowledge of MLOps practices, including CI/CD for ML, model versioning, and automated evaluation
• Exposure to observability and monitoring for machine learning systems
• Experience with LLM-based use cases or applied generative AI work

Inclusion and accommodations

Tinder emphasizes a workplace that values different perspectives, backgrounds, and lived experiences. The company welcomes applicants across all sexes, gender identities, races, ethnicities, disabilities, and other identities. Candidates who do not match every qualification are still encouraged to apply if their experience is transferable. Reasonable accommodations are available for applicants who need support during the application, testing, or interview process by contacting the Talent Acquisition Partner.

Compensation

The base salary range for this role is $145,000 to $165,000 per year. The final offer may vary based on the role scope, responsibilities, candidate experience, education or training, job-related skills, internal equity, and market or business factors. Compensation is tied to the Palo Alto location and may be adjusted geographically if approval is granted to work from a different city or state.