Pathway
France
R&D ML Engineer
- AI
- Artificial Intelligence
- Deep Learning
- GIT
AI Summary
Optimize cloud infrastructure for ML training/inference, automate ML/LLM pipelines, and manage model versioning/reproducibility. Requires Linux, Kubernetes, cloud (AWS/GCP/Azure), and Python expertise. Focus on scalability, CI/CD, and production monitoring for AI models.
Key Highlights
Optimize cloud infrastructure for ML training/inference (GPUs, distributed compute)
Automate ML/LLM pipelines (data ingestion, training, deployment) with CI/CD
Monitor model performance and data drift in production
Key Responsibilities
Optimize cloud infrastructure for ML workloads (GPUs, distributed compute)
Automate ML/LLM pipelines (data ingestion, training, validation, deployment)
Manage model versioning, reproducibility, and traceability
Monitor model performance and data drift in production
Collaborate with ML engineers, software engineers, and platform teams
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Technical Skills Required
Benefits & Perks
Intellectually stimulating work environment
Remote work with options to visit offices in Palo Alto, Paris, or Wroclaw
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Nice to Have
Contributions to open-source projects (e.g., Linux kernel)
Experience with academic grid/cluster computing scaling efforts
Experience with competitive achievements (e.g., sports championships)
Job Description
We are currently searching for a Machine Learning DevOps with experience in cloud and compute cluster management, scaling infrastructures, and Linux administration.
Our development, ML training, and production environment is in the cloud, using several major cloud providers. We need support in managing and automating the processes, and scaling the infrastructure to growing team and production needs.
You Will
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