Digital Trust Centre (DTC) is looking for a candidate to join them as a Research Engineer II.
Key Responsibilities:
- Conduct cutting-edge research in large language models, translating theoretical algorithms, frameworks, and methodologies into practical, working prototypes that demonstrate potential product applications.
- Collaborate closely with researchers and engineers to design and implement system architectures and software solutions that transition research findings into scalable, deployable products.
- Develop and build tools and frameworks to facilitate the transfer of LLM capabilities to industry partners, showcasing the practical value and impact of the research outcomes.
- Create and maintain comprehensive technical documentation, including white papers, presentations, and tutorials, to disseminate knowledge to a broader audience and enhance overall expertise in these emerging areas.
- Engage with international research communities and partners to stay abreast of the latest advancements in machine unlearning, contributing to discussions, collaborations, and initiatives that elevate Singapore’s position in the global AI and privacy research landscape.
Job Requirements:
- Minimum Masters’s degree in computer science/ engineering or related fields.
- Proficiency in Python is a must. Experience with other programming languages such as Java, C/C++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous.
- Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large language models (LLMs), including tasks such as data preprocessing, feature extraction, model training, and evaluation.
- Strong knowledge of machine learning and deep learning techniques, including knowledge graphs, machine unlearning, and AI testing.
- Proficiency in working with common Linux distributions (e.g., Ubuntu, CentOS) and familiarity with shell scripting and command-line tools.
- Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes) is a must.
- Experience with version control systems (e.g., Git) and collaborative development tools.
- Experience in developing ML systems from end to end, including data exploration, feature engineering, model training/evaluation will be advantageous.
- Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders, bridging the gap between research and practical application.
- Strong analytical and problem-solving skills, with a focus on developing innovative solutions for LLMs.
- Self-motivated and able to work independently, managing multiple tasks and projects in a fast-paced environment.
- Strong collaborative skills, with experience working in cross-functional teams.
- Keen attention to detail and commitment to high-quality deliverables.
- Understanding of ethical considerations and best practices in AI research, particularly concerning data privacy and security.
- Ability to code-switch effortlessly between talking business and talking tech, and can help stakeholders, engineers, and businesses easily understand difficult research tech concepts.
- Experience in AI model testing methodologies, including robustness, fairness, and explainability assessments, as well as understanding data privacy and security considerations in AI.
- Good understanding of relational database and Unix shell scripting skills.
We regret to inform that only shortlisted candidates will be notified.
