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# AI Developer

- **Company:** Atos Corp.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Databases, Data Visualization, Python (Programming Language), PostgreSQL, Machine Learning, MongoDB, NumPy, Power BI, Tensorflow, SQL Databases, Tableau (Software), Jupyter Notebook, Google Cloud, Cloud Platform System, Pytorch, Git, Pandas, Matplotlib, Scikit Learn, Machine Learning Operations, Software Version Control
- **Published:** August 1, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p8u1ho7hmh

## About the Role

* Experience A solid track record with at least 2 years of commercial experience with AI and at least 5+ years of commercial experience in a Data Scientist or similar role.
 * Programming Skills Strong proficiency in Python and its core Data Science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow/PyTorch).
 * Experience with Retrieval-Augmented Generation (RAG) techniques
 * Database Proficiency Fluency in SQL with hands-on experience querying relational (e.g., PostgreSQL) and non-relational (e.g., MongoDB) databases.
 * Machine Learning A strong theoretical understanding and practical application of machine learning algorithms and best practices.
 * Data Visualization The ability to create impactful data visualizations using tools like Matplotlib, Power BI or Tableau.
 * Essential Tools Experience with version control systems (Git) and development environments like Jupyter Notebooks/JupyterLab.
 * Cloud Experience (Bonus) Familiarity with a major cloud platform (AWS, GCP, Azure) is a significant advantage.

Language Skills

 * B2/C1 English mandatory

## Description

* Develop AI/ML Solutions Design, build, and deploy end-to-end machine learning models to solve complex business challenges (e.g., classification, regression, clustering, forecasting).
 * Data Exploration & Analysis Proactively identify opportunities in large datasets, perform exploratory data analysis, and generate actionable insights to guide business strategy.
 * Collaboration & Innovation Work closely with a team of data engineers, AI specialists, and business stakeholders to define project requirements and deliver robust, data-driven solutions.
 * Communicate Insights Translate complex findings into clear, concise language and compelling visualizations for both technical and non-technical audiences.
 * Model Lifecycle Management Take ownership of the entire model lifecycle, from prototyping and validation to deployment, monitoring, and continuous improvement.


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