Machine Learning Engineer II

Tinder seeks a Machine Learning Engineer II in Los Angeles, CA (hybrid) to build production machine learning systems that enhance product experiences and drive measurable business impact. This individual contributor role emphasizes modeling and algorithmic innovation, translating product opportunities into ML solutions, running experiments, and deploying models to production.

Responsibilities

• 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

Compensation

USD 145,000 - 165,000 per year

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 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

Technologies

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

Benefits

• Flexible Vacation, 10 Sick Days
• Time off to volunteer and charitable donations matched up to $15,000 annually
• Comprehensive health, vision, and dental coverage
• 100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP)
• 100% paid parental leave including for non-birthing parents and family forming benefits
• Investment in your development: mentorship through MentorMatch, access to 6,000+ online courses via Udemy, and an annual $3,000 development stipend
• Wellness support: mental health services via Modern Health, paid concierge medical membership, pet insurance, fitness membership 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 such as AWS and containerized environments such as Kubernetes
• Familiarity with ML model serving frameworks such as TensorFlow Serving, TorchServe, Triton Inference Server, or Ray Serve
• Experience with feature stores, ML data pipelines, and orchestration frameworks such as Airflow
• Understanding of MLOps practices including CI/CD for ML, model versioning, and automated evaluation
• Exposure to observability and monitoring for ML systems
• Exposure to LLM related use cases or applied generative AI projects

Where you will work

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