Gen AI Architect

JR United Kingdom; London; On-site; GBP 80,000 - 120,000; Full time

Job summary

A leading company in the UK is seeking a highly skilled Generative AI Architect to join their dynamic team. The role involves designing advanced AI systems, developing algorithms, and ensuring ethical AI practices. Candidates should have strong programming skills and experience with AI technologies.

Qualifications

• Experience with large language models (LLMs) and prompt engineering.
• Strong programming skills in Python, R, or Java.

Responsibilities

• Design and develop architecture for AI systems including data storage and processing.
• Develop and implement advanced AI algorithms and models.

Skills

Problem-Solving

Analytical Skills

Communication

Education

Bachelor's or Master's in Computer Science

Tools

TensorFlow

PyTorch

Keras

AWS

Azure

Google Cloud

Job description

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We are seeking a highly skilled Generative AI Architect to join our dynamic team and drive the development of advanced AI systems capable of learning, reasoning, and making decisions autonomously.

Key Responsibilities:

1. AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the system's scalability, flexibility, and efficiency to handle large algorithms.
2. Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning, and neural networks. Continuously evaluate and improve these algorithms to enhance system performance and accuracy.
3. Data Integration: Identify relevant data sources and design methods for data collection, integration, cleansing, and transformation. Collaborate with data scientists and engineers to ensure the quality and relevance of data for AI model training.
4. Model Training and Evaluation: Train AI models using supervised, unsupervised, or reinforcement learning techniques. Implement evaluation methodologies to measure the performance and effectiveness of trained models. Fine-tune models based on feedback and data insights.
5. Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency.
6. System Integration: Collaborate with software developers and engineers to integrate AI systems into existing platforms or applications. Ensure seamless communication and compatibility between AI components and other software modules.
7. Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage.
8. Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities.
9. Teamwork and Communication: Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to define AI requirements and deliver AI solutions that meet business objectives. Communicate complex AI concepts and solutions effectively to both technical and non-technical audiences.

Mandatory Qualifications/Skills:

• A bachelor's or master's degree or equivalent in computer science, Artificial Intelligence, or related field.
• Experience with large language models (LLMs) and prompt engineering.
• Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks.
• Strong programming skills in languages such as Python, R, or Java.
• Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras.
• Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms.
• Solid understanding of AI concepts, algorithms, and methodologies.
• Knowledge of designing large-scale AI solutions, data integration, cleansing, and transformation techniques.
• Excellent problem-solving and analytical skills, with the ability to think creatively and provide innovative solutions.
• Strong communication and collaboration skills to work effectively in multidisciplinary teams. Knowledge of ethical AI practices and laws is a plus.

Preferred Skills:

• Knowledge of NVIDIA CUDA, cuDNN, TensorRT, and experience with NVIDIA GPU hardware and software stack.
• Understanding of HPC and AI workloads.
• Familiarity with Big Data platforms and technologies, such as Hadoop or Spark.