Gen AI Solutions Engineer
⚲ Bengaluru
Do uzgodnienia
Wymagania
- automation
- Deployment
- API (Application Programming Interface)
- Machine Learning (ML)
- Performance optimization
- training
- Use Cases
- Artificial Intelligence (AI)
- SQL
- Python
Opis stanowiska
Introduction & Summary:
We are seeking an experienced Gen AI Solutions Engineer to develop and support AI use cases in Dataiku that align with business needs. The ideal candidate should possess 6-8 years of experience and demonstrate a strong ability to translate business requirements into scalable AI/ML solutions.
Main Responsibilities:
The successful candidate will be responsible for:
• Understanding business requirements and translating them into scalable and technically feasible AI/ML solutions.
• Designing, developing, and deploying robust, scalable, and efficient machine learning and generative AI solutions.
• Building end-to-end data pipelines including data ingestion, pre-processing, model training, evaluation, and deployment.
• Developing expertise in Dataiku DSS, including flow design and automation.
• Implementing advanced architectures such as RAG, K-RAG, and CAG, with knowledge of their end-to-end design and implementation.
• Building scalable and production-ready AI solutions with proper versioning, monitoring, and performance optimization.
• Implementing efficient data pipelines using Python, SQL, and Streamlit, along with API integrations within Dataiku.
• Maintaining and understanding the CICD pipeline.
Key Requirements:
• Proficiency in Python and SQL.
• Hands-on experience with Dataiku and Streamlit.
• Familiarity with advanced architectures, specifically RAG, K-RAG, and CAG.
• Understanding of LLM concepts.
Other Details:
This role is focused on the integration of AI solutions in a data-centric environment and may offer remote work flexibility. The expected engagement duration is long-term, reflecting ongoing business needs.
We are seeking an experienced Gen AI Solutions Engineer to develop and support AI use cases in Dataiku that align with business needs. The ideal candidate should possess 6-8 years of experience and demonstrate a strong ability to translate business requirements into scalable AI/ML solutions.
Main Responsibilities:
The successful candidate will be responsible for:
• Understanding business requirements and translating them into scalable and technically feasible AI/ML solutions.
• Designing, developing, and deploying robust, scalable, and efficient machine learning and generative AI solutions.
• Building end-to-end data pipelines including data ingestion, pre-processing, model training, evaluation, and deployment.
• Developing expertise in Dataiku DSS, including flow design and automation.
• Implementing advanced architectures such as RAG, K-RAG, and CAG, with knowledge of their end-to-end design and implementation.
• Building scalable and production-ready AI solutions with proper versioning, monitoring, and performance optimization.
• Implementing efficient data pipelines using Python, SQL, and Streamlit, along with API integrations within Dataiku.
• Maintaining and understanding the CICD pipeline.
Key Requirements:
• Proficiency in Python and SQL.
• Hands-on experience with Dataiku and Streamlit.
• Familiarity with advanced architectures, specifically RAG, K-RAG, and CAG.
• Understanding of LLM concepts.
Other Details:
This role is focused on the integration of AI solutions in a data-centric environment and may offer remote work flexibility. The expected engagement duration is long-term, reflecting ongoing business needs.
🔍 Dekoder Ogłoszenia
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develop and support AI use cases in Dataiku that align with business needs
Może oznaczać zarówno tworzenie innowacyjnych rozwiązań, jak i głównie utrzymanie i drobne modyfikacje istniejących procesów w Dataiku.
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strong ability to translate business requirements into scalable AI/ML solutions
Oczekuje się, że kandydat będzie potrafił zrozumieć potrzeby biznesowe i przełożyć je na konkretne rozwiązania techniczne, co może wymagać dużej elastyczności i komunikatywności.
🔴
Designing, developing, and deploying robust, scalable, and efficient machine learning and generative AI solutions
Zakres obowiązków jest szeroki i obejmuje cały cykl życia modelu, od koncepcji po produkcję, co może być bardzo wymagające.
🟡
Developing expertise in Dataiku DSS, including flow design and automation
Oznacza to głębokie zanurzenie się w narzędzie Dataiku, co może być zarówno szansą na rozwój, jak i ograniczeniem, jeśli kandydat preferuje inne technologie.
🔴
Implementing advanced architectures such as RAG, K-RAG, and CAG, with knowledge of their end-to-end design and implementation
Wymaga to nie tylko znajomości koncepcji, ale także praktycznego doświadczenia w budowaniu i wdrażaniu tych złożonych architektur, co może być trudne do zdobycia bez wcześniejszego kontaktu.