1 day ago
Boston, MA, USA or New York, NY, USASenior / Staff+
H1B sponsor
Base Salary
$229k - $364k/yr
Responsibilities
- Build and scale data infrastructure for personalized recommendations and music discovery.
- Design streaming pipelines that convert user interactions and content signals into fresh recommendation features.
- Develop offline and online feature computation, storage, and serving infrastructure for model training and inference.
- Enable recommendation experimentation through reliable impression and interaction logging.
- Own streaming and batch infrastructure architecture, reliability, observability, monitoring, alerting, lineage, and automated recovery.
- Build modular, testable, and observable data workflows using orchestration frameworks.
- Define event schemas, data contracts, and ingestion patterns with backend and product engineers.
- Optimize pipelines and storage for performance, cost, scalability, latency, and freshness across AWS and Snowflake.
- Implement infrastructure as code and contribute to standards for schema evolution, data quality, and pipeline reliability.
- Lead technical design discussions, shape data platform architecture, mentor engineers, and improve engineering quality.
Requirements
- 7+ years of relevant experience in software engineering, data infrastructure, or distributed systems.
- Strong programming skills, preferably in Python, and experience 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 products.
- Understanding of feature computation, online/offline 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 and observable systems with 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 and make pragmatic technical decisions in ambiguous environments.
- Track record of owning scalable infrastructure and improving engineering practices.
- Preferred experience with AWS Kinesis, Firehose, Lambda, S3, Glue, Snowflake, Dagster, Airflow, dbt, Terraform, or similar tools.
- Must be eligible to work in the US.
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 and generous commuter allowance.
- In-office lunch five days per week.
- Requires working from the Cambridge, MA, or New York, NY office five days per week.
Tech Stack
Categories
Data EngineeringML Engineering
About Suno
Suno builds an AI music-creation platform and Suno Studio, tools that let anyone generate complete songs without instruments, used by hobbyists and professional artists. It operates a consumer subscription business and is exploring additional monetization products. Founded in 2022 and headquartered in Cambridge, Massachusetts, the privately held company targets the global music and entertainment market.