Applied ML Engineer: Fine-tuning (Remote-First)

Best AI Tools Wiki; Paris; Hybride; EUR 85 000 - 120 000; Plein temps

Avantages offerts par ce poste

Equity stake

Remote-first

Annual retreats

Conference budget

Relocation support

Résumé du poste

Best AI Tools Wiki is seeking an Applied ML Engineer to develop and improve fine-tuning capabilities for our language models. You will build fine-tuning infrastructure, design data pipelines, and help customers customize models for their use cases.

Ideal candidates have 3+ years of ML engineering experience, strong experience in LLM fine-tuning (LoRA, QLoRA, full), and proficiency in Python and PyTorch. You will collaborate with product teams and customers to deliver robust, scalable solutions.

Qualifications

• 3+ years of ML engineering experience.
• Strong experience with LLM fine-tuning (LoRA, QLoRA, full).
• Proficiency in Python and PyTorch.
• Understanding of training data curation and quality.
• Experience with model evaluation and benchmarking.

Responsabilités

• Develop fine-tuning infrastructure for language models.
• Design and implement data pipelines for model fine-tuning.
• Improve fine-tuning capabilities across products.
• Help customers customize models for their use cases.
• Benchmark and evaluate model performance.

Connaissances

ML engineering

LLM fine-tuning

Python

PyTorch

Data curation

Model evaluation

Description du poste

Best AI Tools Wiki is seeking an Applied ML Engineer to develop and improve fine-tuning capabilities for our language models. You will build fine-tuning infrastructure, design data pipelines, and help customers customize models for their use cases.

Ideal candidates have 3+ years of ML engineering experience, strong experience in LLM fine-tuning (LoRA, QLoRA, full), and proficiency in Python and PyTorch. You will collaborate with product teams and customers to deliver robust, scalable solutions.