AI/ML Architect
Do uzgodnienia
Wymagania
- Python
- TensorFlow
- PyTorch
- LLM
Opis stanowiska
We are seeking an experienced AI Architect to lead the design and implementation of cutting-edge AI solutions, ensuring they are safe, reliable, and high-performing.
The ideal candidate will have a strong foundation in state-of-the-art AI/ML technologies and a proven ability to guide projects strategically, ensuring that AI solutions are robust, ethical, and deliver significant business value.
- AI Strategy & Leadership: Lead the end-to-end development of advanced AI models and frameworks (including large language models, transformers, and agent-based systems), aligning AI initiatives with business goals. Provide technical leadership to data science and engineering teams, and set strategic direction for AI projects.
- Architectural Design: Design and oversee the integration of AI components such as LLMs, transformer architectures, retrieval-augmented generation (RAG) workflows, and vector databases into scalable solutions. Establish standards for model architecture and pipeline optimisation to ensure robustness and efficiency.
- Evaluation & Safety: Define and enforce rigorous evaluation protocols for AI models, including performance metrics, validation techniques, and safety checks. Ensure all AI systems meet reliability standards, ethical guidelines, and regulatory requirements for responsible AI usage.
- MLOps & Deployment: Guide the development of MLOps pipelines for continuous training, testing, and deployment of models in cloud environments. Oversee infrastructure decisions (without bias to specific platforms) to guarantee that AI services are scalable, secure, and maintainable in production.
The ideal candidate will have a strong foundation in state-of-the-art AI/ML technologies and a proven ability to guide projects strategically, ensuring that AI solutions are robust, ethical, and deliver significant business value.
- AI Strategy & Leadership: Lead the end-to-end development of advanced AI models and frameworks (including large language models, transformers, and agent-based systems), aligning AI initiatives with business goals. Provide technical leadership to data science and engineering teams, and set strategic direction for AI projects.
- Architectural Design: Design and oversee the integration of AI components such as LLMs, transformer architectures, retrieval-augmented generation (RAG) workflows, and vector databases into scalable solutions. Establish standards for model architecture and pipeline optimisation to ensure robustness and efficiency.
- Evaluation & Safety: Define and enforce rigorous evaluation protocols for AI models, including performance metrics, validation techniques, and safety checks. Ensure all AI systems meet reliability standards, ethical guidelines, and regulatory requirements for responsible AI usage.
- MLOps & Deployment: Guide the development of MLOps pipelines for continuous training, testing, and deployment of models in cloud environments. Oversee infrastructure decisions (without bias to specific platforms) to guarantee that AI services are scalable, secure, and maintainable in production.
🔍 Dekoder Ogłoszenia
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lead the design and implementation of cutting-edge AI solutions
Oczekuje się, że będziesz odpowiedzialny za cały proces od koncepcji po wdrożenie, co może oznaczać dużą odpowiedzialność i presję.
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ensure they are safe, reliable, and high-performing
Wymagania dotyczące bezpieczeństwa, niezawodności i wydajności mogą być bardzo wysokie i trudne do spełnienia w praktyce, zwłaszcza w szybko rozwijających się technologiach AI.
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proven ability to guide projects strategically
Może oznaczać, że będziesz musiał podejmować kluczowe decyzje strategiczne z ograniczonym wsparciem lub zasobami.
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aligning AI initiatives with business goals
Może oznaczać, że będziesz musiał tłumaczyć złożone koncepcje techniczne na język biznesowy i udowadniać wartość biznesową projektów AI, co bywa wyzwaniem.
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Ensure all AI systems meet reliability standards, ethical guidelines, and regulatory requirements for responsible AI usage.
Wymaga to dogłębnej wiedzy i ciągłego monitorowania zmieniających się przepisów i standardów etycznych, co może być czasochłonne i skomplikowane.