Développeur.euse sénior, Plateforme de données ML

Job summary

You will be responsible for architecting, scaling, and maintaining high-performance data pipelines that power next-generation machine learning models. This role involves bridging the gap between AI research and engineering by treating the data platform as a product for internal researchers.

Job details

You will be responsible for architecting, scaling, and maintaining high-performance data pipelines that power next-generation machine learning models. This role involves bridging the gap between AI research and engineering by treating the data platform as a product for internal researchers. Candidates must hold a bachelor's degree in a relevant field and possess over 5 years of experience in designing and managing large-scale distributed data systems. Proficiency with tools such as Ray, Apache Spark, and containerization technologies is essential for this role.

What you’ll do

You will be responsible for architecting, scaling, and maintaining high-performance data pipelines that power next-generation machine learning models. This role involves bridging the gap between AI research and engineering by treating the data platform as a product for internal researchers.

Requirements

Candidates must hold a bachelor's degree in a relevant field and possess over 5 years of experience in designing and managing large-scale distributed data systems. Proficiency with tools such as Ray, Apache Spark, and containerization technologies is essential for this role.

Listed skills

• Kubernetes · Preferred
• Docker · Preferred
• Machine learning · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Data Engineering
• Distributed Systems
• Ray
• Apache Spark
• Kubernetes
• GPU Optimization
• Data Pipelines
• Python
• Software Architecture
• Data Governance
• Workflow Orchestration
• Docker
• Vector Databases
• Data Lineage
• High-Performance Computing

Job areas

• Technology
• Data & Analytics
• Software
• Science & Research
• Engineering

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