Employment Information
As a Data Scientist specializing in deep learning at GoTo Financial, you will tackle complex challenges in computer vision, voice, and text processing. You will lead the development and deployment of advanced AI models that directly impact our key business products. Your responsibilities will include enhancing our systems with cutting-edge deep learning models and ensuring they are scalable in a production environment. This role offers the opportunity to drive innovation, solve critical business challenges, and shape the future of AI-driven financial solutions at GoTo Financial.
What you will do
- Work with data like images, videos, audio, and text etc.
- Design, train, optimize, and deploy deep learning models with GPU.
- Develop comprehensive unit tests and documentation, and rigorously evaluate and benchmark model performance and quality.
- Communicate effectively between the business team and the engineering team to gather and implement project requirements.
- Own the end-to-end process, from defining the technical problem to deploying the solution in collaboration with engineers.
- Stay current with the latest advancements in deep learning and AI technologies.
What you will need
- 3+ years of experience in deep learning, particularly with (prio 1)computer vision, voice, and text processing.
- Proficient in data preprocessing, model training, evaluation, and optimisation.
- Practical experience in applying deep learning to solve real business problems, with models successfully deployed and used in production environments. (NLP, chat GPT)
- Proficient with deep learning frameworks such as PyTorch, and familiar with Python, C++, and inference engines like NCNN.
- Experience with cloud platforms like GCP or AWS, and working knowledge of Android/iOS is a plus.
- Strong communication skills to understand business needs and effectively convey analytical solutions.
- Ability to write clear and concise technical documentation.
- A Master's or PhD in Computer Science, Data Science, AI, or a related field.