Reflection AI

1 day ago

Member of Technical Staff - Engineering Lead, Data Ingestion

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Lead Reflection’s Data Ingestion team responsible for turning the web and other large-scale sources into structured, versioned, auditable training corpora. You’ll build, mentor, and grow data ingestion engineers; guide technical and architectural decisions across web crawl, extraction/normalization pipelines, and data lakes; and stay hands-on with the stack. Partner with research, data quality, and partnerships teams to connect ingestion choices to downstream model impact and run evaluation experiments.

Location: San Francisco, London, New York

Workplace: Onsite

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Manager level

Key Responsibilities

•Build, mentor, and grow a high-performing team of data ingestion engineers.
•Provide front-line leadership across the ingestion stack: web crawling/acquisition, extraction/normalization pipelines, and data lakes for versioned delivery.
•Stay hands-on and contribute as an individual contributor by maintaining deep stack familiarity.
•Manage day-to-day execution by prioritizing work and running data acquisition/ingestion campaigns in a fast-paced environment.
•Guide technical and architectural decisions for scalability, reliability, auditability, cost, and dataset versioning/delivery, partnering with research and data quality teams.

Pay and Benefits

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionLifeEquityPaid LeaveParental LeaveMeal AllowanceWellness Stipend

Key Requirements

•Experience building, mentoring, and growing data or infrastructure engineering teams while staying technically hands-on.
•Deep experience building web-scale data acquisition or ingestion systems with ownership of production pipelines at multi-TB to PB scale.
•Strong coding ability with credibility to earn technical trust.
•Expertise in at least one area: web crawling & acquisition, large-scale extraction & ingestion pipelines, or data lakes/corpus storage & delivery, with ability to learn the rest.
•Fluency with large-scale data tooling including distributed compute (Ray/Beam/Spark), orchestration (Airflow/Prefect), and data formats (Parquet/JSONL/WARC).

Experience:Data infrastructureLarge-scale dataLLM dataWeb-scale dataData ingestion

Skills:Technical leadershipMentorshipPrioritizationCommunicationExecution

Tech Stack:RayBeamSparkAirflowPrefectParquetJSONLWARCObject storesLakehouseRobots.txtLLMs

Company Brief

Reflection AI

Builds frontier autonomous AI systems focused on autonomous coding agents (product: Asimov) to create organizational superintelligence, founded by former DeepMind/Google researchers and hiring across SF, NYC, London.

Industry: AI & Machine Learning

Company Size: Small (11 to 50 employees)

Growth: Growth Stage Startup

Funding: Series A

Headquarters: San Francisco, United States

Founded: 2024

Website LinkedIn Glassdoor

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Reflection AI

1 day ago

Member of Technical Staff - Engineering Lead, Data Ingestion

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: San Francisco, London, New York

Workplace: Onsite

Employment Type: Full time

Job Function: Administration & Executive Assistance

Seniority: Manager level

Key Responsibilities

•Build, mentor, and grow a high-performing team of data ingestion engineers.
•Provide front-line leadership across the ingestion stack: web crawling/acquisition, extraction/normalization pipelines, and data lakes for versioned delivery.
•Stay hands-on and contribute as an individual contributor by maintaining deep stack familiarity.
•Manage day-to-day execution by prioritizing work and running data acquisition/ingestion campaigns in a fast-paced environment.
•Guide technical and architectural decisions for scalability, reliability, auditability, cost, and dataset versioning/delivery, partnering with research and data quality teams.

Pay and Benefits

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionLifeEquityPaid LeaveParental LeaveMeal AllowanceWellness Stipend

Key Requirements

•Experience building, mentoring, and growing data or infrastructure engineering teams while staying technically hands-on.
•Deep experience building web-scale data acquisition or ingestion systems with ownership of production pipelines at multi-TB to PB scale.
•Strong coding ability with credibility to earn technical trust.
•Expertise in at least one area: web crawling & acquisition, large-scale extraction & ingestion pipelines, or data lakes/corpus storage & delivery, with ability to learn the rest.
•Fluency with large-scale data tooling including distributed compute (Ray/Beam/Spark), orchestration (Airflow/Prefect), and data formats (Parquet/JSONL/WARC).

Experience:Data infrastructureLarge-scale dataLLM dataWeb-scale dataData ingestion

Skills:Technical leadershipMentorshipPrioritizationCommunicationExecution

Tech Stack:RayBeamSparkAirflowPrefectParquetJSONLWARCObject storesLakehouseRobots.txtLLMs

Company Brief

Reflection AI

Industry: AI & Machine Learning

Company Size: Small (11 to 50 employees)

Growth: Growth Stage Startup

Funding: Series A

Headquarters: San Francisco, United States

Founded: 2024

Website LinkedIn Glassdoor