Sr. Software Engineer, Machine Learning Infrastructure

The Role:The Engineering team is responsible for building innovative features and resilient systems that bring people together. We're always experimenting with new features to engage with our members. Although we are a high-scale tech company, the member-to-engineer ratio is very high—making the level of impact each engineer gets to have at Tinder enormous.The machine learning infrastructure team develops infrastructures and systems that support end-to-end machine learning development cycle, including training, serving, feature management, model management, monitoring and observability, etc.We are looking for a Sr. Software Engineer to help shape and develop the future of Tinder’s Machine Learning infrastructure. Your work will empower teams across Tinder to rapidly test hypotheses and scale their experiments on massive datasets, reaching hundreds of billion data points. In this role, you’ll collaborate closely with multiple machine learning teams to drive impactful innovation.Where you’ll work:This is a hybrid role and requires in-office collaboration twice per week. This position is located in Palo Alto, CA.In this role, you will:Build robust and scalable infrastructure to support the diverse needs of machine learning engineers across all Tinder business units.Set future technical directions for Tinder’s ML infrastructure.Mentor junior team members.Leverage your experience to drive best practices in ML and data engineering.Collaborate with cross functional agile teams of software engineers, data engineers, ML experts, and others in building new product features.Develop and maintain robust infrastructure for large language models (LLMs).Develop strategies for model evaluation and quality assurance.You’ll need:5+ years of experience with developing platforms related to machine learning training, serving, feature management, experimentation, etc.Bachelor’s degree in Computer Science, Engineering, Technology, or a related field.Strong understanding of data-driven development, reliability principles, and responsible experimentation practices.Extensive experience with big data processing and storage frameworks such as Hadoop, Spark, Flink, Cassandra, or Kafka.Solid foundation in machine learning concepts like regression, classification, clustering, training, testing, validation, and performance measurement.Proven ability to lead cross-functional initiatives, communicate effectively, and collaborate in team-oriented environments.A strong background in distributed systems, cloud computing, and MLOps, with hands-on experience in working with transformers and other deep learning architectures.Bridge the gap between cutting-edge research and production-ready AI systems.Salary Range:$180,000-$220,000a yearFactors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.

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