Data Scientist

Sansaone; West-Vlaanderen; Sur place; EUR 65 000 - 90 000; Plein temps

Résumé du poste

Sansaone seeks a Data Scientist to design and develop AI and data science solutions, building and maintaining ML pipelines and deploying models primarily on premises. You will implement best practices in programming and ML, monitor ML systems, and keep up with MLOps advancements.

Knowledge of security, ethics, and legal considerations is a plus. You will work across on-premise and cloud environments, with emphasis on scalable ML systems and robust data architectures.

Qualifications

• Master's or doctoral degree in computer science, AI, or equivalent.
• Minimum of 3 years of experience in data science, MLOps, and ML.

Responsabilités

• Design and develop AI and Data Science solutions to meet operational needs.
• Develop ML pipelines and monitor/maintain them.
• Deploy AI models on-premises and ensure best practices in programming and ML.
• Conduct tech monitoring to stay up-to-date with ML/AI developments.
• Awareness of security, ethical, and legal aspects.

Connaissances

ML & MLOps

Big data

On-prem & Cloud

End-to-end ML system design

Formation

Master's or PhD in CS/AI

Outils

Docker

Kubernetes

Kubeflow

MLflow

Hugging Face

PyTorch

TensorFlow

Scikit-learn

PostgreSQL

MySQL

Neo4j

Milvus

OpenCV

vLLM

Description du poste

Job Description

As a Data scientist, you will directly participate in the design and development of AI and Data Science solutions to meet the operational and tactical needs. You will be responsible for developing machine learning pipelines, as well as their monitoring and maintenance. You will also be responsible for deploying AI models for the organization, primarily on-premises. You will ensure the implementation of best practices in programming and machine learning within your projects. You will conduct technological monitoring to stay up-to-date with the latest developments in MLOps and machine learning. An awareness of security, ethical, and legal aspects is a plus.

As a Data scientist, you will directly participate in the design and development of AI and Data Science solutions to meet the operational and tactical needs. You will be responsible for developing machine learning pipelines, as well as their monitoring and maintenance. You will also be responsible for deploying AI models for the organization, primarily on-premises. You will ensure the implementation of best practices in programming and machine learning within your projects. You will conduct technological monitoring to stay up-to-date with the latest developments in MLOps and machine learning. An awareness of security, ethical, and legal aspects is a plus.

Desired Profile

You hold a master's or doctoral degree in computer science, AI, or equivalent and can demonstrate a minimum of 3 years of experience in data science, MLOps, and ML.

You Have Expertise In The Following Areas

• On-premise and cloud development: Expertise in the development and deployment of AI solutions on-premise and in the cloud (Azure, AWS, GCP).
• 3+ years of industry experience: You have 3+ years of experience in the world of ML, MLOps and big data with a focus on large-scale deployment.
• Theoretical background and practical expertise: in the field of ML and deep learning.
• Database Paradigm (SQL & NoSQL): Advanced knowledge of relational and non-relational databases (SQL and NoSQL), including PostgreSQL, MySQL, Milvus, Neo4j, etc.
• ML MLOps: Demonstrable experience in deploying ML models and expertise in MLOps.
• Focus on big data: experience in the exploitation of large structured and unstructured datasets .
• Containerization and deployment: Experience with Docker and Kubernetes, as well as
• orchestration tools like Kubeflow. Proficiency with ML pipelines (Kubeflow, MLflow, SageMaker, etc.).
• CI/CD for ML: Proficiency in implementing CI/CD for ML models and associated code.
• Data Storage: Experience with different data storage solutions (data lakes, data warehouse houses, object storage (S3))
• System architecture: Ability to design an end-to-end ML system taking into account scalability, robustness, maintenance and hardware constraints.

Hard Skill

• Databases: MySQL, PostgreSQL, Neo4j, Milvus
• AI/ML Frameworks & Tools: Hugging Face, MLflow, PyTorch, TensorFlow, Scikit-learn, OpenCV, vLLM
• Programming Languages: Python; R is a plus
• Orchestration & Containerization: Docker, Kubernetes, Kubeflow
• Cloud Platforms: Microsoft Azure, AWS
• Code & Model Versioning: MLflow, Git, GitHub, GitLab

Skills

• Azure
• Docker
• GIT
• GitHub
• Gitlab
• Hugging face
• Kubeflow
• Kubernetes
• kite
• MLflow
• MySql
• Neo4J
• PostgreSQL
• Python
• Pytorch
• Ruff
• TensorFlow