Job Purpose
The job purpose of a Lead AI Engineer is to provide technical leadership and expertise in the field of artificial intelligence (AI) within SMRT. This role involves overseeing the development, implementation, and management of AI solutions and projects.
Duties & Responsibilities
- Involved in designing, developing, and implementing AI solutions that address specific business problems or opportunities. This includes selecting appropriate algorithms, models, and technologies to achieve desired outcomes.
- Stay up-to-date with the latest advancements in AI research and technologies, and apply this knowledge to drive innovation within their projects and the organization as a whole.
- Manage the end-to-end lifecycle of AI projects. This involves defining project scope, setting goals, creating timelines, managing resources, and ensuring projects are delivered on time and within budget.
- Work closely with cross-functional teams, including software engineers, data scientists, product managers, and domain experts, to understand requirements and ensure that AI solutions align with business goals.
- Tackle complex challenges related to data quality, model accuracy, scalability, and deployment. They use their expertise to identify and overcome obstacles that arise during the development and implementation process.
- Ensuring the quality and reliability of AI systems is a critical aspect of the job. Responsible for testing, validating, and iterating on AI models to enhance their performance and robustness.
Qualifications & Work Experience
- Degree in computer science, artificial intelligence, machine learning, data science, or a related field is preferred.
- Minimum 10 years of experience with end-to-end AI solution development, including data preprocessing, model training, validation, and deployment.
- Ability to understand current/changing business processes, participation in defining application and platform functionality.
- Proficiency in programming languages commonly used in AI, such as Python, Java, or C++.
- Strong understanding of machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and AI tools.
- Proficiency in project management methodologies and tools to oversee and deliver AI projects on time and within budget.
- In-depth understanding of data manipulation, feature engineering, and data preprocessing techniques. Familiarity with data storage and processing technologies (e.g., SQL, NoSQL, distributed computing).
- Exceptional communication, problem solving and cross-group collaboration skills
- Knowledge of Rail Industry would be highly advantageous.
