Skill diminta
AWSCI/CDCustomer ServiceCustomer SupportDockerFastAPIFlaskGitHub ActionsGraphQLJavaScriptKubernetesLogisticsMongoDBPostgreSQLPyTorchPythonRedisSQLScikit-learnTensorFlowTypeScript
Deskripsi
- AI Engineer (LLM / Generative AI)
- Role Overview
- We are looking for a highly motivated
- AI Engineer
- who is passionate about building production-ready AI applications using
- Large Language Models (LLMs), Machine Learning, Computer Vision, Recommendation Systems, and Generative AI
In this role, you will collaborate closely with Product, Engineering, Design, Marketing, and Operations teams to develop AI-powered solutions that enhance customer experience, optimize business operations, and support scalable product growth.
- Key Responsibilities
- AI Product Development
- Design, build, and deploy AI-powered customer experiences.
- Develop recommendation engines for personalized product suggestions.
- Build intelligent search and ranking systems to improve search relevance.
- Develop conversational AI applications and virtual assistants.
- Build AI-powered customer support automation solutions.
- Create AI-driven personalization features.
- Develop AI solutions for inventory optimization and demand forecasting.
- Design scalable AI services for production environments.
- Generative AI & Large Language Models (LLMs)
Develop applications using
- OpenAI APIs
- Anthropic Claude
- Google Gemini
- Open-source LLMs (Llama, Mistral, Qwen)
Build and implement
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents
- Function Calling
- Multi-agent Workflows
Develop AI-powered features such as
- AI Shopping Assistant
- AI Advisor
- Product Description Generator
- Customer Service Copilot
- AI Content Generator
- Marketing Copy Generator
- Social Media Content Generator
- Recommendation Systems
- Design and develop intelligent recommendation engines, including:
- Personalized Product Recommendations
- Similar Products
- Frequently Bought Together
- Trending Products
- Content-Based Recommendation
- Collaborative Filtering
- Hybrid Recommendation Models
- Computer Vision
Develop AI-powered computer vision solutions, including
- Visual Search
- Similar Image Search
- Product Recognition
- Image Embeddings
- Object Detection
- Classification Models
- Color, Pattern, and Style Recognition
- Automated Product Tagging
- Machine Learning
Build, train, deploy, and maintain ML models for
- Customer Segmentation
- Purchase Prediction
- Customer Lifetime Value (LTV)
- Churn Prediction
- Demand Forecasting
- Inventory Forecasting
- Dynamic Pricing
- Fraud Detection
- Marketing Attribution
- AI Infrastructure & MLOps
Design and maintain scalable AI infrastructure, including
- Vector Databases
- Embedding Pipelines
- Model Deployment
- Model Monitoring
- Feature Stores
- ML Pipelines
- Experiment Tracking
- Prompt Management
- AI APIs
- Data Engineering
Work with large-scale datasets including
- Product Catalog Data
- Customer Behavior
- Clickstream Data
- Search Logs
- Purchase History
- Inventory Data
- Logistics Data
- Marketing Data
- Required Qualifications
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field.
- Minimum 3 years of experience in AI/ML Engineering, preferably within a product or startup environment.
- Strong Python programming skills.
- Experience deploying AI models into production environments.
- Hands-on experience with AWS or other cloud platforms.
- Strong backend and API development experience.
- Experience building scalable distributed systems.
- Solid understanding of software engineering best practices.
- Technical Skills
- Programming
- Python
SQL
- JavaScript / TypeScript (preferred)
- AI & Machine Learning
- PyTorch
- TensorFlow
- Scikit-learn
- Hugging Face Transformers
- LangChain
- LlamaIndex
- OpenAI SDK
- Anthropic SDK
- Databases
- PostgreSQL
- Redis
- MongoDB
- Pinecone
- Weaviate
- Milvus
- pgvector
- Cloud & DevOps
AWS
- Docker
- Kubernetes (preferred)
- GitHub Actions
CI/CD
- Backend
- FastAPI
- Flask
- REST APIs
- GraphQL (preferred)
- Nice to Have
- Experience in e-commerce or retail technology.
- Experience building recommendation systems at scale.
- Knowledge of Computer Vision and Multimodal AI.
- Experience fine-tuning open-source foundation models.
- Familiarity with A/B testing and experimentation.
- Understanding of MLOps and model lifecycle management.
- Experience working in high-growth startup environments.
- What You'll Build
- AI Shopping Assistant
- Personalized Product Recommendation Engine
- AI Search & Semantic Search
- Visual Search
- Customer Support AI
- AI Content Generation Platform
- Marketing Automation Solutions
- Inventory Forecasting Models
- Dynamic Pricing Engine
- AI Analytics & Business Intelligence
- Intelligent Merchandising Tools