Application Architect
7 months ago
Overview:
**Key Responsibilities**:
- Collaborate with Business / Practice Units, Relevant Stakeholders and Customers to understand business goals and determine AI requirements.
- Design and develop AI architectures, frameworks, and algorithms that can support large-scale and sophisticated AI solutions.
- Evaluate and select appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability.
- Own the development and implementation of AI models, ensuring consistency to standard processes in machine learning and deep learning.
- Develop and maintain AI pipelines, incorporating data cleaning, pre-processing, feature engineering, model training, and validation processes.
- Conduct regular code reviews and provide technical guidance to junior members of the team.
- Collaborate with infrastructure teams to ensure smooth deployment and monitoring of AI models in production environments.
- Document AI architectures, design decisions, and technical specifications for reference and knowledge sharing.
**Qualifications**:
- Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field.
- Experience working as an AI Technical Lead or Architect, working knowledge of machine learning, deep learning, and natural language processing (NLP) techniques.
- Experience working on LLMs, Model Training & Evaluation, Performance Benchmarking.
- Proficiency in programming languages such as Python, Java, or C++, and familiarity with popular AI libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).
- Experience in designing and implementing large-scale AI solutions, including data ingestion, storage, processing, and deployment.
- Good understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms.
- Excellent problem-solving and analytical skills, with the ability to break down complex problems into actionable components.
- Strong communication and teamwork skills, with the ability to work effectively within multi-functional teams.
- Ability to stay updated with the latest advancements in AI technologies, frameworks, and platforms.
- Knowledge of ethical considerations and responsible AI practices is a plus.
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