Member of Technical Staff - Data Platform
Reflection2 months ago
Responsibilities
- Design ingestion and orchestration patterns for batch and streaming workloads.
- Build scalable compute and storage foundations for large-scale data processing.
- Develop reproducible pipelines with versioning, backfills, and isolated execution environments.
- Establish data quality, lineage, metadata, and governance signals for trusted production decisions.
- Manage cost and performance through guardrails, budgets, partitioning, clustering, and continuous tuning.
- Unify ingestion, processing, and workflow management across research, training, and production environments.
- Debug and operate production-grade data pipelines and systems at scale.
Requirements
- Strong data engineering background with experience shipping production-grade pipelines at scale.
- Experience designing and owning end-to-end data systems for large-scale batch and streaming workloads.
- Ability to debug complex pipeline failures, optimize cost and performance, and maintain data quality.
- Comfort working in a high-agency, fast-paced, collaborative environment across research and infrastructure boundaries.
- Interest in zero-to-one system building and creating the data backbone for open-weight AI systems.
Benefits
- Top-tier compensation and equity structured for global talent, including stock options.
- Comprehensive medical, dental, vision, and life insurance with an annual wellness allowance.
- Lunch and dinner provided daily in the office.
- 22 weeks of paid parental leave for birthing, non-birthing, adoptive, and surrogate parents.
- Unlimited paid time off in the U.S. and 30 days of vacation in the U.K.
- Visa sponsorship and support for applicable long-term immigration pathways.
- Regular off-sites, happy hours, and team celebrations.
- The role may be subject to U.S. export control authorization requirements.
Tech Stack
Categories
Data Engineering
About Reflection
Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. Our team previously built frontier LLMs at labs like DeepMind, OpenAI, and Anthropic. We believe AI should be built in the open, with transparent research and collaborative development. That means giving enterprises, governments, and sovereign entities true ownership and control of AI that performs at the highest level. Our mission: make intelligence open and accessible to all.