Machine Learning Engineer II

Tinder offers a hybrid position in Los Angeles, CA with a salary range of $145,000 to $165,000 per year. This Machine Learning Engineer II role centers on building production ML systems that enhance product experience and drive measurable business impact. As an individual contributor, you will focus on modeling and algorithmic innovation, translating product opportunities into ML solutions, running experiments, and deploying models to production. In addition to competitive compensation, Tinder provides a comprehensive benefits package and a culture that values development, wellbeing, and collaboration.

Responsibilities

• Transform product and business challenges into well defined ML problems with clear success metrics
• Build, train, evaluate, and refine production ML models
• Collaborate with software engineers and ML infrastructure engineers to deploy models and improve reliability, scalability, and performance in production
• Design offline evaluations and online experiments to measure model impact
• Contribute to feature engineering, data preparation, training pipelines, and model monitoring
• Write clean, maintainable, production ready code and participate in design and code reviews
• Communicate technical findings, trade offs, and recommendations clearly to both technical and non technical partners

Requirements

• 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 a solid understanding of how modern ML systems are developed and operated
• Proficiency in Python and at least one additional language such as Java, Kotlin, Go, Scala, or similar
• Solid understanding of machine learning fundamentals, including model training, evaluation, and experimentation
• Strong communication skills and the ability to collaborate across functions
• Self motivated, proactive, and comfortable owning well scoped problems

Technologies

• Python, Java, Kotlin, Go, Scala
• Spark, Flink
• AWS, Kubernetes
• TensorFlow Serving, TorchServe, Triton Inference Server, Ray Serve
• Airflow

Benefits

• Flexible vacation and 10 sick days
• Volunteer time off with charitable donations matched up to $15,000 annually
• Comprehensive health, vision, and dental coverage
• 100% 401(k) employer match up to 10% and an Employee Stock Purchase Plan (ESPP)
• 100% paid parental leave including for non-birthing parents and family forming benefits
• Development support through MentorMatch, access to 6,000+ Udemy courses, and an annual $3,000 professional development stipend
• Wellness benefits including mental health support via Modern Health, concierge medical membership, pet insurance, fitness subsidy, and commuter subsidy
• Free Tinder Gold subscription

Nice to Have

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

Where You'll Work

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