Job Summary: We are seeking a hands-on AI Architect to join our AI Tech Team. The candidate will be responsible for spearheading the design and development of AI solutions within the Cloud frameworks, with a focus on Google Cloud Platform (GCP). This role is crucial to our goal of providing cutting-edge AI solutions that deliver substantial benefits to the scientific community.
Key Responsibilities:
• Lead the design, development, and implementation of AI solutions in the GCP Cloud environment (AWS is a plus).
• Lead AI problem framing, exploratory data analysis, data preprocessing, model training and tuning, and model serving.
• Develop the AI solution prototyping. • Design and develop MLOps and oversee the implementation. • Design and develop AI model serving solutions and oversee the implementation.
• Contribute to key projects, including manuscript analysis, editor recommendation systems, publication recommendation, quality checks in line with client standards, topic analysis, etc.
• Utilize advanced NLP technologies, open source LLMs (BERT, Llama, or the likes), and cloud[1]native AI technologies for text learning and topic learning.
• Work with a diverse tech stack, including Cloud-native AI, NLP, Python programming, TensorFlow, TFX, Kubeflow, PyTorch, Scikit-learn, BERT, AI embedding techniques, model tunning techniques, model validation techniques, feature engineering technologies, data engineering, etc.
• Mentor junior developers. Qualifications: • 10+ year hand-on experience of building AI/ML solutions.
• Proven experience in AI development and cloud-native AI solution in GCP Cloud (AWS is a plus).
• Proficiency in ML practice and MLOps, including ML pipeline, AI embedding, model tunning, model validation, data validation, feature engineering, data engineering, model monitoring and ML automation.
• Proficiency in TensorFlow, TFX, Kubeflow, PyTorch, Scikit-learn, BERT, LLMs, etc,
• Proficiency in Topic Modelling, NLP and open source LLMs.
• Experience in rapid prototyping and presenting AI solution design. • Experience in creating AI explanation, feature-based and example-based.
‘• Experience in turning research and concept into business products, working with business stakeholders to develop products that work at scale. • Ability to work collaboratively in a dynamic team environment.
• Understand modern software engineering best practices, TDD, BDD, CI/CD, automation, etc.
• General architecture of Cloud infrastructure is a plus.
• Bachelor's degree in computer science, Information Technology, or related field. Advanced or professional certifications in Cloud are advantageous. What We Offer: • A challenging and rewarding role in a leading scientific organization. • Opportunity to work on groundbreaking AI projects with a global impact. • Competitive compensation. • A supportive environment fostering
