AI & Production Deployment: Development, implementation, and transition of AI-based solutions into production use within industrial manufacturing environments
Contribute to design language system standards, components, and documentation, applying strong design craft and technical fundamentals as the foundation of the role.
AI Inference & Model Serving: Deploy and optimize production model-serving solutions through Cloudera AI Inference across on-premises, private-cloud, and public-cloud environments. Validate model, runtime, and GPU compatibility, alongside API behavior, concurrency, and reliability.
Educational Background & Technical Foundations Pursuing a degree in Computer Science, Data Science, Engineering, or a related field Strong fundamentals in programming (preferably Python) and SQL Basic understanding of data structures, algorithms, and software engineering principles 2. Data & AI Knowledge Familiarity with data processing concepts (ETL/ELT, data modeling, data cleaning) Exposure to machine learning fundamentals (e.g., supervised/unsupervised learning, model evaluation) Experience with common data/ML libraries (e.g., Pandas, NumPy, scikit-learn) is a plus 3. Tools & Platform Exposure Exposure to cloud platforms (e.g., AWS, Azure, or GCP) and modern data ecosystems is advantageous Familiarity with databases (SQL/NoSQL) and data warehousing concepts (e.g., Snowflake, BigQuery, Databricks) 4. Problem-Solving & Mindset Strong analytical thinking and problem-solving skills Ability to break down complex problems into structured solutions Eagerness to learn and adapt in a fast-paced, technology-driven environment 5. Communication & Collaboration Good communication skills, with the ability to explain technical concepts clearly Team player with a proactive and ownership-driven attitude Ability to work with cross-functional teams (analytics, business stakeholders)
Support the achievement of sales targets by developing and maintaining a healthy pipeline and guiding customers through end-to-end sales cycles, from discovery through to agreement;
Large language Model Algorithm Development: Build domain-specific large language models (LLM/MLLM) for e-commerce, integrating domain knowledge to rapidly apply models to business scenarios.
Responsible for the design, development, and iteration of AI Agents in TikTok Shop business scenarios, covering the full cycle from requirement analysis to architecture design, development, and launch, delivering intelligent and efficient product experiences for merchants and users;
Discovery and analysis: Interview stakeholders, document business processes and pain points, analyse data and readiness, and identify suitable AI, GenAI and agentic use cases.
Responsible for the design, development, and iteration of AI Agents in TikTok Shop business scenarios, covering the full cycle from requirement analysis to architecture design, development, and launch, delivering intelligent and efficient product experiences for merchants and users;
Large language Model Algorithm Development: Build domain-specific large language models (LLM/MLLM) for e-commerce, integrating domain knowledge to rapidly apply models to business scenarios.
Our mission is to enable next-generation AI capabilities through tightly integrated hardware and software innovation across imaging and vision systems. We believe meaningful advances in Edge AI require optimization across the entire technology stack, from machine learning algorithms and deployment toolchains to processor architecture and silicon implementation.
Drive Holistic Onboarding: Coordinate and execute the onboarding journey for retail frontline staff and corporate executive-level new hires. You will partner with Operations Management to ensure the "Buddy System" is effectively implemented at the store level for seamless integration
Develop and validate models using operational sensor data for failure prediction, asset(mechanical and electrical equipment) degradation monitoring, early-warning detection, remaining useful life estimation, and time-to-threshold forecasting.