Lead Platform Engineer: Large-Scale Data & AI Systems

Scale AI, Inc.; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Scale AI, Inc. is seeking an experienced Platform Engineer to lead the design and development of core data storage, streaming, caching, and indexing platforms.

You will shape foundational systems and work across Scale to support world-class RLHF, data generation, model evaluation, safety and alignment initiatives. You will collaborate with cross-functional teams to refine requirements, implement new features, and drive engineering best practices while mentoring others in scalable data

Qualifications

• 5+ years of full-time engineering experience with back-end data platforms.
• Experience building large-scale data storage, streaming, and warehousing systems.
• Proven track record mentoring and leading teams on complex projects.
• Excellent communication skills and ability to translate technical concepts to non-technical stakeholders.
• Experience with Kubernetes and public cloud deployments.
• Deep understanding of distributed systems and data platforms.

Responsibilities

• Drive design, implementation, and reliability of foundational data platforms and systems.
• Collaborate with cross-functional teams to define and deliver new features.
• Identify and implement improvements to development processes and tools.
• Present technical information to stakeholders and provide guidance on development approaches.

Skills

Back-end systems

Distributed data storage

Streaming/warehousing

Database tech (MongoDB, Postgres)

Kubernetes & cloud

Communication & mentoring

Tools

Kinesis

Flink

Spark

ElasticSearch

Redis

Trino/Presto/Snowflake

Job description

Scale AI, Inc. is seeking an experienced Platform Engineer to lead the design and development of core data storage, streaming, caching, and indexing platforms.

You will shape foundational systems and work across Scale to support world-class RLHF, data generation, model evaluation, safety and alignment initiatives. You will collaborate with cross-functional teams to refine requirements, implement new features, and drive engineering best practices while mentoring others in scalable data