AI Scientist

Roles and Responsibilities

• Conduct requirements elicitation, translating these into clear and organized business requirement, and prioritizing development and delivery in close coordination with key stakeholders and management.
• Lead the design and implementation of AI/ML solutions using state-of-the-art large models (e.g., GPT, LLaMA, BERT), focusing on scenarios such as chatbot, intelligent Q&A, agent automation, semantic search, summarization, and decision support.
• Fine-tune, prompt-engineer, or customize pre-trained models on domain-specific data to improve task performance.
• Build and maintain pipelines for data collection, preprocessing, annotation, and model training/evaluation, ensuring robustness and scalability.
• Evaluate model performance through metrics, A/B testing, and human-in-the-loop validation to ensure alignment with business KPIs.
• Collaborate with data engineers and MLOps to deploy AI models into production environments with appropriate monitoring, feedback loops, and fallback mechanisms.
• Support the construction of enterprise knowledge graphs, domain-specific embeddings, and data augmentation strategies to enrich LLM outputs.
• Research, assess, and apply the latest developments in generative AI, retrieval-augmented generation (RAG), and multimodal AI to business scenarios.
• Prepare technical documentation, including system architecture, model specifications, API definitions, and user guidelines to support maintainability and knowledge transfer.
• Present insights, results, and opportunities to both technical and non-technical stakeholders through clear storytelling and visualizations.
• Drive internal AI innovation initiatives and support talent enablement through training, demo sessions, and workshops.
• Stakeholder Management: communicate and negotiate with key stakeholders and process owners to achieve a win-win solution given the constraints on costs, resources, skills, time, and other priorities.
• Project Management: plan, initiate, and manage constraints and deliverables to successfully complete and deliver project results.
• Quality Assurance: proactively manage incidents, problems, issues, and risks by implementing various techniques, methods, and best practices.
• Training and Support: Coordinate resources to provide training and support to business users to ensure appreciation and proper use of system functions and capabilities.
• Documentation and Knowledge Management: organize and prepare documentation of knowledge materials, including requirements specifications, solution design, flow charts, user manuals, etc., to ensure that all relevant information are recorded, stored, accessible and reusable.
• Improvement Initiatives. Research, assess, and employ best practices in data management, analysis, and controls, and continually enhance system functions and capabilities.

Job Skills & Qualifications

1. Bachelor's/College Degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, Information Management, Engineering (Computer/Telecommunication) or equivalent courses.

2. Solid experience in building and deploying NLP/LLM applications using frameworks like Hugging Face Transformers, LangChain, LlamaIndex, OpenAI API, etc.

3. Proficiency in Python and key ML libraries: PyTorch, TensorFlow, Scikit-learn, Numpy, Pandas.

4. Familiarity with prompt engineering, instruction tuning, fine-tuning, and knowledge retrieval techniques (e.g., RAG, vector databases).

5. Experience working with large-scale datasets, knowledge bases, or document corpora in enterprise settings.

6. Strong grounding in ML/DL concepts and experience applying them to real-world problems, preferably in telecommunications, customer service, or enterprise workflow automation.

7. Experience with relational and non-relational databases such as Hive, Spark, MySQL, and vector DBs (e.g., FAISS, Weaviate, Pinecone) is a plus.

8. Excellent communication skills in English (both written and verbal); Mandarin proficiency is a plus.

9. Self-driven, fast learner, with strong problem-solving and critical thinking skills.

10. Willingness to work onsite in BGC, Taguig City.

11. Mastery in at least one programming language, such as: Python/Java/Scala, etc., and proficiency in numpy, pandas, sklearn and other tools.

12. Willing to work onsite in BGC, Taguig City