Senior / Staff Software Engineer, Data Infrastructure
About The Position
Suno is hiring Senior and Staff Software Engineers to build and scale foundational data systems for its data platform and personalized recommendations. The role designs and operates infrastructure that ingests, processes, and serves petabytes of data for analytics, experimentation, machine learning, music recommendations, and discovery. Working across Data, ML, Engineering, and Product teams, the engineer builds pipelines, feature infrastructure, and low-latency data services that turn user interactions and content signals into reliable, fresh data for model training and real-time personalization. The engineer will help set the long-term architecture for Suno’s data platform, balancing scalability, reliability, latency, and cost. The role owns major systems from design through production operation, leads technical direction across teams, and builds observable, extensible systems that help teams experiment and improve music discovery.
Requirements
- At least 7 years of relevant experience in software engineering, data infrastructure, or distributed systems.
- Strong programming skills, preferably in Python, and experience building and operating production-grade distributed systems.
- Deep experience building and operating real-time streaming and batch processing systems.
- Experience building data or serving infrastructure for recommendations, personalization, search, or similar ML-powered product experiences.
- Understanding of feature computation, online/offline data consistency, and production ML latency and freshness requirements.
- Experience with streaming and cloud data infrastructure such as Flink, Kinesis, Kafka, or equivalent technologies.
- Experience designing reliable, observable systems, including monitoring, logging, alerting, and recovery.
- Strong understanding of data modeling, schema evolution, and data quality.
- Ability to collaborate with ML, data, and product engineering teams, make pragmatic technical decisions, and deliver in ambiguous environments.
- Ownership mindset and a track record of delivering scalable infrastructure and improving engineering practices.
- Excitement about music, creativity, AI, and infrastructure that helps people create and discover music.
- Must be eligible to work in the United States.
- Must work from the Cambridge, Massachusetts or New York, New York office five days per week.
Nice To Haves
- Experience with AWS services such as Kinesis, Firehose, Lambda, S3, and Glue.
- Experience with Snowflake or a similar cloud data warehouse, including performance and cost optimization.
- Experience with Dagster, Airflow, or similar orchestration frameworks.
- Experience with dbt for transformations, testing, and modular data modeling.
- Experience with Terraform or similar infrastructure-as-code tools.
Responsibilities
- Build and scale data infrastructure for personalized recommendations and music discovery in partnership with ML and product engineers.
- Design streaming pipelines that transform user interactions and content signals into fresh features for recommendation models.
- Develop infrastructure to compute, store, and serve features for offline model training and online inference, maintaining consistency, reliability, and low latency.
- Enable recommendation experimentation with reliable impression and interaction logging to evaluate models and measure recommendation quality.
- Own the architecture and reliability of core streaming and batch infrastructure.
- Build and maintain modular, testable, observable data workflows and orchestration using Dagster.
- Partner with backend and product engineers to define event schemas, data contracts, and production-system ingestion patterns.
- Improve data pipeline reliability and observability through monitoring, alerting, lineage tracking, and automated recovery.
- Optimize pipelines and storage for performance, cost efficiency, and scalability across AWS and Snowflake.
- Implement infrastructure as code to manage AWS and Snowflake resources consistently and reproducibly.
- Establish data platform standards for schema evolution, data quality, and pipeline reliability.
- Lead technical design discussions and shape the future architecture of Suno’s data platform.
- Mentor engineers and improve engineering quality, reliability, and maintainability.
Benefits
- Company equity package.
- 401(k) with 3% employer match and Roth 401(k).
- Medical, dental, and vision insurance, with PPO, HSA, and FSA options.
- 11 paid holidays, unlimited PTO, and sick time.
- 16 weeks of paid parental leave.
- Creative education stipend.
- Generous commuter allowance.
- In-office lunch five days per week.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
