AirflowAWSCloudGoogle Cloud PlatformNumpyPandasPythonPyTorchScikit-LearnSQLTensorflowAIMachine LearningMLLLMRAGLangChainAgenticTensorFlowscikit-learnNumPyMLOpsMLflowSnowflakeGCPGoogle CloudBedrockCI/CDRemote Work
About this role
Role Overview
Define and evolve our infrastructure to allow for better ML and AI capabilities, with a focus on LLM-based and agentic systems.
Contribute to the development and expansion of our agentic AI framework powered by AWS Bedrock, enabling both internal tools and customer-facing features.
Identify, source, and refine datasets to allow tuning models, powering retrieval pipelines, or expanding agentic workflows.
Pre-process data by using techniques such as data cleaning, feature engineering, and transformation.
Train, evaluate, and deploy both LLM-based systems and traditional machine learning models into production.
Monitor, debug, and continuously improve deployed models and AI tools.
Support machine learning usage throughout the company, including selecting the right modeling approach for the use case (LLM vs. traditional ML).
Support the integration and use of LLMs, including approaches such as fine-tuning, prompt tuning, and retrieval-augmented generation (RAG), to improve accuracy.
Requirements
5+ years of experience as a Data Scientist or Machine Learning Engineer.
Experience working with LLMs (e.g., prompt engineering, fine-tuning, retrieval-augmented generation).
Experience working with Agents for Amazon Bedrock AgentCore or similar agent setups.
Strong understanding of machine learning algorithms, statistical methods, and data preprocessing techniques.
Experience with cloud platforms for model training and deployment, especially AWS.
Proficiency in Python, including experience with libraries such as LangChain, Scikit-Learn, NumPy, Pandas, and PyTorch/TensorFlow.
Proficiency in SQL and experience working with data warehouses (e.g., Snowflake, GCP).
Knowledge of MLOps best practices, including CI/CD pipelines, model monitoring, and versioning (e.g., MLflow, Airflow).
Experience deploying models to production and supporting them post-deployment.
Fluency in English.
Tech Stack
Airflow
AWS
Cloud
Google Cloud Platform
Numpy
Pandas
Python
PyTorch
Scikit-Learn
SQL
Tensorflow
Benefits
🌎 International team
🎉 Fun team building events
🖥️ €40/month for remote work
🌴 Flexible working time
👩💻 Home office budget up to €1500
👩🏻⚕️ 100% of an Alan Blue subscription (french-based contracts)
🍜 Lunch vouchers
€8 (50% The Phantom Company) / worked day (french-based contracts)