At a Glance
- Tasks: Lead and mentor a team to build scalable data infrastructure for AI systems.
- Company: Join Reflection, a pioneering research lab making AI accessible for everyone.
- Benefits: Top-tier salary, stock options, unlimited vacation, and comprehensive health benefits.
- Other info: Dynamic team culture with opportunities for professional growth and collaboration.
- Why this job: Make a real impact in the future of AI while working with cutting-edge technology.
- Qualifications: 8+ years in engineering with strong data pipeline experience and leadership skills.
The predicted salary is between 90000 - 110000 £ per year.
Our Mission: Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI.
About the role: Reflection is building the trusted data backbone for the world's most capable open-weight AI systems. The Data Platform team builds and operates the core data systems and pipelines that power our research, training, and production environments, unifying ingestion, processing, and orchestration across the entire data lifecycle so every team can move faster. We're looking for a front-line technical leader to build, mentor, and grow this team. You'll guide its technical direction while staying hands-on; this is a role for someone who has earned deep technical credibility as an engineer and now multiplies it through a team. You'll work closely with our research team to understand what high-velocity experimentation actually needs, and turn that into reliable, reproducible, scalable data infrastructure.
What you'll do:
- Build, mentor, and grow a team of ~10 exceptional data platform engineers, hiring, coaching, and raising the bar with every person you add.
- Guide the technical direction across the platform: ingestion and orchestration patterns for batch and streaming workloads, scalable compute and storage foundations, and reproducible pipelines with versioning, backfills, and isolated execution environments.
- Work closely with research, training, and production teams to enable high-velocity experimentation on a unified data layer.
- Establish trusted data quality, lineage, and governance signals so teams can make confident production decisions.
- Keep cost and performance predictable through guardrails, budgets, and continuous system tuning.
- Stay hands-on: design reviews, architecture decisions, and code where it matters most.
What you'll work with:
- Compute & orchestration: Spark, Flink, Beam, Airflow, Dagster, Kafka, PubSub
- Storage & analytics: data lake and warehouse architectures, Parquet, Iceberg, Delta Lake, BigQuery, Snowflake
- Metadata & data quality: lineage systems, metadata management, Great Expectations, reproducibility systems
- Cost & performance: partitioning strategies, clustering, cost optimization, SLA-driven pipelines
About you:
- 8+ years of engineering experience with a strong data engineering foundation — you've shipped and owned production-grade pipelines at large scale (tens of TBs to PBs daily).
- A track record as a staff/principal-level individual contributor before moving into leadership — you earn the technical trust of a strong team.
- You've managed and grown a team (~5–10), or clearly demonstrated the leadership readiness to build one quickly — while staying technically embedded.
- Deep in at least one of: ingestion & orchestration at scale, storage and processing engines (lakehouse formats, query engines), or data quality/lineage/reproducibility systems — with working breadth across the others.
- Fluent in the modern data stack; you've built new systems from zero rather than maintained legacy ones.
- Thrive in a high-agency, fast-paced environment; bias toward action and impact.
- Collaborative, clear communicator, comfortable working across research and infrastructure boundaries.
What We Offer:
- Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.
- Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options.
- Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance.
- Meals: Lunch and dinner are provided in the office daily.
- Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys.
- Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K.
- Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.
- Team building: We have regular off-sites, happy hours, and team celebrations.
Export Control Notice: This position may require access to technology or source code subject to the U.S. Export Administration Regulations. Any offer of employment for this role may be conditioned on the Company's ability to provide the candidate with access to such technology or source code in compliance with applicable U.S. export control laws, which may require the Company to seek government authorization.
Member of Technical Staff - Engineering Lead, Compute Platform in London employer: Reflection AI
At Reflection, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our commitment to employee growth is evident through our mentorship opportunities and the chance to lead a talented team in a fast-paced environment, all while enjoying top-tier benefits such as unlimited paid time off and comprehensive health coverage. Located in a vibrant area, we offer a unique opportunity to contribute to groundbreaking AI research while ensuring a supportive work-life balance.
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We think this is how you could land Member of Technical Staff - Engineering Lead, Compute Platform in London
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We think you need these skills to ace Member of Technical Staff - Engineering Lead, Compute Platform in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Reflection AI. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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