DATA ENGINEER

About Atos Group

Atos Group is a global leader in digital transformation with c. 67,000 employees and annual revenue of c. €10 billion, operating in 61 countries under two brands — Atos for services and Eviden for products. European number one in cybersecurity, cloud and high performance computing, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is the brand under which Atos SE (Societas Europaea) operates. Atos SE is listed on Euronext Paris.

The purpose of Atos Group is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

Generative AI Data Engineer

Company: Atos
Location: Toronto ,Canada
Job Type: Fulltime

Salary: 100k-110k CAD

Generative AI Knowledge: Solid understanding of generative AI models and algorithms, and their applications in solving complex business problems.

Skills: Release & Deployment,MS Azure DevOps Services,Microservices,MS Azure Cloud Services,Large Language Model Ops (LLMOps),Generative AI, Preferred candidates must have experience in data indexing, chunking and optimizing RAG patterns.

Release Management: Experience with scaled-up release management for AI applications using CICD pipelines for automated testing and deployment

Technical skills: Experience with Azure cloud environment with Databricks, Data Factory, Storage account, Proficiency in Python programming & SQL

Microservice Architecture: Experience in building microservice-based architecture for GenAI solutions.

Data Processing: Experience in working with large-scale data sources in complex environments and implementing scalable and efficient data processing pipelines.

Azure Expertise: Expert knowledge in full stack Azure development, including experience with Azure cloud platforms in the context of GenAI solution development and deployment, and familiarity with common tools in data science.

Platform Experience: Nice to have knowledge of optimizing model performance and ensuring scalability to handle expected workloads. Familiarity with LLM models deployment in the cloud environment. Ability to set up monitoring for model performance, including metrics like accuracy, latency, and throughput.

Communication and Collaboration: Strong communication and ability to effectively collaborate with multi-functional teams and partners.

Motivation and Results-Driven: Highly motivated and results-driven, comfortable in handling changes, and delivering results in complex situations.

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