Artificial Intelligence Engineer
4 weeks ago
The AI Engineer will:
- Lead the company's AI initiatives and drive the adoption of the latest generative AI (GenAI) technologies and languages
- Implement and manage chatbots, advisory systems, and other AI-powered solutions to enhance the company's products and services
- Research and evaluate modern AI technology stacks, platforms, and tools to identify the most suitable solutions for the company's needs
- Design, develop, and deploy production-ready AI-powered applications and systems
- Collaborate with cross-functional teams, including engineering, product, and business stakeholders, to understand requirements and deliver effective AI-driven solutions
- Present AI initiatives and solutions to stakeholders, demonstrating their value and impact on the business
In this role, we are looking for someone with:
- Extensive experience in implementing and managing AI-powered applications, including chatbots, advisory systems, and other AI-based solutions
- Proficient in the latest GenAI technologies, languages, and frameworks, such as GPT-3, DALL-E, Whisper, and Stable Diffusion
- Proven track record of delivering production-ready AI solutions and presenting them effectively to stakeholders
- Strong understanding of modern AI technology stacks, including cloud-based AI platforms, machine learning frameworks, and data engineering tools
- Excellent problem-solving, critical thinking, and analytical skills to identify and address complex AI-related challenges
- Effective communication and collaboration skills to work with cross-functional teams and stakeholders
- Bachelor's degree in Computer Science, Data Science, or a related field; advanced degree preferred
Good to have:
- Experience in deploying and managing AI-powered applications in a production environment
- Familiarity with DevOps practices and tools for AI/ML model deployment and monitoring
- Knowledge of natural language processing (NLP), computer vision, and other AI/ML domains
- Hands-on experience with popular AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers)
- Understanding of ethical considerations and responsible AI practices
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