Staff Software Engineer, Data Platform
$252k - $315k • Remote • San Francisco, CA; New York, NY
Posted 2mo ago
Job Location
San Francisco, CA; New York, NY
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
Scale is at the forefront of the AI revolution, developing data engines and technologies that power the world's leading LLMs and generative models. This role is on the Platform Engineering team, responsible for the foundational data infrastructure that supports these cutting-edge AI products. You will lead the design and development of core data storage, streaming, caching, and indexing platforms, gaining exposure to the rapidly evolving AI landscape across various industries. The work involves driving architecture, implementation, and reliability of these critical systems, collaborating with stakeholders, and mentoring junior engineers.
Responsibilities
- Drive the architecture, design, implementation, and reliability of foundational data platforms and systems.
- Collaborate with cross-functional teams to define, design, and deliver new features.
- Identify and drive improvements to current programming practices, including process enhancements and tool upgrades.
- Present technical information to teams and stakeholders.
- Provide technical leadership, uphold engineering standards, and mentor junior engineers.
Requirements
- 8+ years of full-time engineering experience post-graduation.
- Specialties in back-end systems, specifically building large-scale data storage, streaming, and warehousing systems.
- Extensive experience with database technologies (MongoDB, Postgres).
- Extensive experience with streaming/processing solutions (Kinesis, Flink, Spark).
- Extensive experience with indexing/caching solutions (ElasticSearch, Redis).
- Extensive experience with data query engines (Trino, Presto, Snowflake).
- Track record of mentoring and leading teams in successful projects.
- Excellent communication and collaboration skills, with ability to translate complex technical concepts.
- Experience with containerization & deployment technologies like Kubernetes.
- Experience with various public cloud offerings.
- Deep understanding of distributed systems, cloud platforms, and data systems.
- Experience driving cross-functional collaboration and communication at an organizational level.
Benefits
- Base salary
- Equity
- Comprehensive health, dental, and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous PTO
- Commuter stipend