At a Glance
- Tasks: Design and develop advanced AI systems, algorithms, and neural networks.
- Company: Join a cutting-edge social network focused on innovative AI solutions.
- Benefits: Enjoy flexible work options, competitive pay, and a vibrant team culture.
- Why this job: Be at the forefront of AI technology, making impactful contributions to society.
- Qualifications: Bachelor's or master's in computer science or related field; strong programming skills required.
- Other info: Opportunity to work with the latest AI technologies and collaborate with diverse teams.
The predicted salary is between 43200 - 72000 £ per year.
We are seeking a highly skilled Generative AI Architect to join our dynamic team and drive the development of advanced AI systems that have capabilities to learn, reason and make decisions autonomously.
Key Responsibilities:
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 BigData platforms and technologies, such as Hadoop or Spark.
Gen AI Architect employer: JR United Kingdom
Contact Detail:
JR United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Gen AI Architect
✨Tip Number 1
Familiarise yourself with the latest advancements in generative AI technologies. Follow industry leaders and read up on recent research papers to understand cutting-edge techniques that could set you apart during discussions.
✨Tip Number 2
Engage with online communities and forums focused on AI and machine learning. Networking with professionals in the field can provide insights into the role and may even lead to referrals or recommendations.
✨Tip Number 3
Prepare to discuss your experience with large language models and prompt engineering in detail. Be ready to share specific examples of projects where you've successfully implemented these technologies.
✨Tip Number 4
Showcase your collaborative skills by preparing examples of how you've worked with cross-functional teams. Highlight your ability to communicate complex AI concepts to both technical and non-technical audiences.
We think you need these skills to ace Gen AI Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI systems architecture, algorithm development, and data integration. Use specific examples that demonstrate your skills with large language models and programming languages like Python or R.
Craft a Compelling Cover Letter: In your cover letter, express your passion for generative AI and how your background aligns with the responsibilities outlined in the job description. Mention any innovative projects you've worked on and your understanding of ethical AI practices.
Showcase Your Technical Skills: Include a section in your application that lists your technical skills, particularly those related to AI libraries and frameworks such as TensorFlow or PyTorch. Highlight any experience you have with cloud computing platforms and deploying AI models.
Prepare for Potential Questions: Anticipate questions related to your experience with neural networks and model training. Be ready to discuss specific algorithms you've developed or optimised, and how you approach problem-solving in AI projects.
How to prepare for a job interview at JR United Kingdom
✨Showcase Your Technical Skills
Be prepared to discuss your experience with large language models, machine learning, and deep learning. Highlight specific projects where you've designed AI systems or implemented algorithms, and be ready to explain the technical details in a way that demonstrates your expertise.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your problem-solving skills. Think of examples from your past work where you encountered challenges in AI development and how you overcame them. This will show your analytical thinking and creativity.
✨Emphasise Collaboration and Communication
Since teamwork is crucial for this role, be ready to discuss how you've collaborated with cross-functional teams in the past. Share examples of how you communicated complex AI concepts to non-technical stakeholders, showcasing your ability to bridge the gap between technical and non-technical audiences.
✨Stay Updated on AI Trends
Research the latest advancements in AI technologies and frameworks before your interview. Being knowledgeable about current trends and innovations will not only impress your interviewers but also demonstrate your commitment to continuous learning in the field of AI.