Senior ML Data Engineer — Remote, Scalable Data Pipelines

Bright Vision Technologies; Tampa (FL); Remoto; USD 100.000 - 150.000; Tempo pieno

Vantaggi offerti da questo lavoro

Remote work

Descrizione del lavoro

Bright Vision Technologies is hiring a ML Data Engineer to design and operate large-scale data systems powering AI training and evaluation pipelines. The role emphasizes data ingestion, transformation, quality assurance, lineage, and high-throughput delivery to diverse ML workloads.

Ideal candidates boast 6+ years in data engineering, strong Python skills, and experience with Spark/Ray/Beam, plus distributed data architectures and CI/CD practices.

Competenze

• 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.

Mansioni

• We are seeking an ML Data Engineer to build and operate large-scale data systems powering AI training pipelines.
• Focus on ingestion, transformation, quality assurance, lineage, and high-throughput data delivery to training jobs.
• Collaborate with software engineers and data scientists to optimize model training efficiency.

Formazione

BSc/MSc CS

Strumenti

Hadoop

Airflow

Descrizione del lavoro

Bright Vision Technologies is hiring a ML Data Engineer to design and operate large-scale data systems powering AI training and evaluation pipelines. The role emphasizes data ingestion, transformation, quality assurance, lineage, and high-throughput delivery to diverse ML workloads.

Ideal candidates boast 6+ years in data engineering, strong Python skills, and experience with Spark/Ray/Beam, plus distributed data architectures and CI/CD practices.