Generative AI Engineer
Role summary
We are seeking a Generative AI Engineer with Data Engineering expertise to join our team in Toronto, Canada. This hybrid role requires a solid understanding of generative AI models and algorithms, with a focus on RAG patterns, data indexing, and chunking. You will be responsible for release management of AI applications using CI/CD pipelines, building microservice-based architectures for GenAI solutions, and implementing scalable data processing pipelines. Proficiency in Python, SQL, and Azure cloud environments (Databricks, Data Factory, Storage account) is essential. The ideal candidate will have experience in full-stack Azure development for GenAI solutions and be comfortable optimizing model performance and scalability.
Hi ,
Hope You are doing great !!
We are currently hiring for the following opportunity that may align with your expertise: please let me know if you are interested or open to the job market so you can reply over the same email or you can directly reach me at mohan@hireontech.com / 214 7719902.
Role – GenAI Engineer with Data Engineering expertise
Location – Canada, Toronto ( Hybrid)
Preferred Skillset:
- Generative AI Knowledge: Solid understanding of generative AI models and algorithms, and their applications in solving complex business problems. Preferred candidate 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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