Bright Vision Technologies
AI Data Infrastructure Engineer
Rol remoto de AI Data Infrastructure Engineering con fit claro de ubicación del candidato.
Publicado10 jun 2026
Países elegibles1 país aceptado
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Estados Unidos
Resumen del rol
AI Data Infrastructure Engineer
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
AI Data Infrastructure Engineer
- Design and operate large-scale data pipelines supporting AI training, evaluation, and continual improvement workflows.
- Build ingestion systems for diverse modalities including text, image, audio, video, and structured signals.
- Implement data cleaning, deduplication, filtering, and quality assurance at petabyte scale.
- Develop dataset versioning, lineage, and provenance tracking systems suitable for reproducible training.
- Build high-throughput data loading systems that maximize GPU utilization during training.
- Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement systems.
- Design storage architectures balancing cost, throughput, and latency across data tiers.
- Build evaluation dataset construction pipelines with strict integrity and contamination controls.
- Implement data privacy, redaction, and consent enforcement throughout the pipeline.
- Collaborate with ML researchers and engineers to align data systems with model development needs.
- Drive observability of data quality, drift, and pipeline health across the AI data estate.
- Optimize cost and performance through compression, format selection, and caching strategies.
- Document data systems, schemas, and operational procedures for broad internal use.
- Stay current with AI data infrastructure research and emerging open-source tools.
AI Data Infrastructure Engineer
- Bachelor’s or Master’s degree in Computer Science or a related field.
- Six or more years of data engineering experience, with significant work supporting ML or AI workloads.
- Strong proficiency in Python and at least one JVM or systems language.
- Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
- Hands-on experience operating petabyte-scale storage and pipeline systems.
- Strong understanding of distributed systems, data modeling, and storage formats.
- Experience with dataset versioning, lineage, and reproducibility for ML workflows.
- Familiarity with high-throughput data loading for accelerator-based training.
- Strong software engineering practices including testing, CI/CD, and code review.
- Excellent communication and cross-functional collaboration skills.
AI Data Infrastructure Engineer
- Experience with multimodal datasets at large scale.
- Familiarity with data quality tooling and dataset evaluation methodology.
- Exposure to privacy-preserving data systems and regulated data handling.
- Open-source contributions to data infrastructure projects.
- Experience supporting frontier model training pipelines.
Roles similares
Mantén una lista de respaldo.
CI/CD USA
Staff Backend Engineer- Grafana Enterprise| US| RemoteGrafana LabsVer rol CI/CD USA
Staff Backend Engineer- Grafana Enterprise| Canada| RemoteGrafana LabsVer rol Python 5 países aceptados
Senior Full Stack EngineerOpsvisVer rol Python 8 países aceptados
Senior Data ScientistMorgan StanleyVer rol Stack
Usa estas tags para comparar roles remotos similares.
Elegibilidad de ubicación
Candidatos deberían aplicar solo cuando el país del perfil aparece aquí.
Tu perfilPaís no definidoInicia sesión para comparar tu país con este rol.
Flujo de contratación
WithMira muestra el rol y luego envía candidatos a la aplicación de la empresa.
1Revisa fit del rol, stack y elegibilidad de ubicación en WithMira.
2Abre la página de aplicación de la empresa desde el link rastreado.
3Guarda el rol o suscríbete a oportunidades similares antes de salir.