Multinational technology group KKCompany Technologies is a pioneer in the field of software services. The company is dedicated to creating values for customers with core businesses of multimedia technologies, digital cloud, and AI applications.

At KKCompany, we believe “Innovation Made Simple,” and technology is the answer to the struggles faced by every industry. Since its establishment two decades ago, KKCompany has expanded its portfolio, including KKBOX, BlendVision and Going Cloud. KKBOX is the world’s first platform bringing legal music streaming service to the public. It utilizes state-of-the-art streaming technology to enable excellent user experience. Our flagship brands and a base of international clients enable us to accumulate extensive data and advance analytical capabilities. The strengths along with our abundant experience in brand management help businesses achieve digital transformation successfully. We serve over tens of millions of consumers and enterprise clients in Asia cross a broad spectrum of industries such as telecommunication, multimedia, online education, fitness, smart retail and more.

KKCompany now has over 500 employees across offices in Tokyo, Singapore, Taipei, Kaohsiung, and Hong Kong.

Our Tech Stack:

• Python, especially with data-related libraries (e.g., Pandas, Numpy) and basic serving framework (e.g., FastAPI for HTTP/WebSocket serving).
• Machine learning domain, RAG (Retrieval-Augmented Generation), image generation technology, recommendation system.
• LangChain and advanced prompting techniques.
• Stable Diffusion and corresponding fine-tuning techniques.
• Search engine, e.g., ElasticSearch, Azure CognitiveSearch, and AWS Kendra.
• AWS tools such as SageMaker, Personalize, Transcribe, etc.
• Databricks and Apache Spark for data engineering tasks.
• GitLab for version control and collaboration.
• MLFlow for experiment management.

Responsibilities:

• Lead the development of innovative machine learning projects, with a focus on RAG applications, image generation solutions, and recommendation systems.
• Participate in the end-to-end machine/deep learning product lifecycle, from problem clarification with customers, business understanding, data collection, data exploration, feature engineering, model training, model fine-tuning, model evaluation, model deployment, model inference, and service monitoring to solve real-world cases.
• Design and maintain robust data pipelines using Databricks and Spark, ensuring efficient data processing and analysis.
• Drive advancements in code maintainability, system scalability, and machine learning model performance.
• Stay up to date in current technologies and state-of-the-art methods.
• Collaborate closely with developers, and product owners to implement cutting-edge AI solutions and fulfill customers’ PoC requirements.
• Mentor team members, promoting a culture of learning and technical excellence.
• Thrive in an agile development process and constructive feedback. Critical thinker, problem solver, team player, time management skills, good interpersonal and communication skills.

Basic Qualifications:

• Experience with NLP-related machine learning development and deployment experience.
• Strong experience in Python programming skill and library, framework like FastAPI, Pandas, NumPy, huggingface, scikit-learn, spacy, etc.
• Experience with writing/designing production code and maintaining the codebase.
• Demonstrated expertise in developing, fine-tuning, and deploying machine learning models, including advanced techniques and platforms.
• Experience with basic GenAI technology, eg. LLM, StableDiffusion, prompting skills, etc.

Preferred Qualifications:

• Experience with AWS data and AI services.
• Investigate and implement robust approaches of NLU, NER, zero/few-shot learning, Intent classification, text generation, question answering, and keyword extraction.
• Experience with information retrieval technologies, eg. search engine, vector search, and similarity/semantic search.
• Experience with LangChain, ElasticSearch, and advanced prompting techniques.
• Experience with RAG Chatbots and image-generation solutions.
• Experience with recommendation system design
• Experience with data engineering.
• Experience with DataOps and MLOps.