Model Monitoring Developer Jobs

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1d ago

Machine Learning Engineer II

Tinder Los Angeles, CA

Los Angeles, CA

1d ago

$145k - $165k/yr Full time Ai Ml Artificial Intelligence Big Data

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Job Description

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.

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