About The Role
Droppii is looking for a versatileSenior AI Engineerto drive intelligence across our e-commerce platform. In this role, you will leverage bothGenerative AI(LLMs) andTraditional ML/DLto build features that solve real business problemsfrom smart conversational assistants to personalized shopping experiences and predictive analytics.
We prioritize candidates who bridge the gap between Research and Productionmeaning you not only understand the math behind the models but also write the high-quality software required to deploy them effectively.
Key Initiatives You Will Lead
- Conversational AI:Building next-gen RAG (Retrieval-Augmented Generation) systems that empower our sellers with instant, accurate knowledge.
- E-commerce Intelligence:developing ML/DL models for core platform features. This includes (but is not limited to)Product Recommendations, Semantic Search, Demand Forecasting, and User Segmentation.
Responsibilities
1. Generative AI & NLP Solutions
- Design and optimizeRAG pipelinesto create context-aware chatbots and assistants using LLMs (OpenAI, Gemini, Open Source models).
- Implement advanced retrieval strategies (Vector Search, Hybrid Search) using tools likeLangChainand vector databases (Chroma, Postgres with pgvector, etc.).
- Experiment with Prompt Engineering and Agentic workflows to handle complex user queries.
2. Applied Machine Learning for E-commerce
- Develop scalable ML/DL models usingPyTorch/TensorFlowto enhance user experience (e.g., Personalization/RecSys) and operational efficiency (e.g., Churn Prediction, Sales Forecasting).
- Handle the full data lifecycle: Exploratory Data Analysis (EDA), Feature Engineering, Model Training, and Evaluation.
- Apply various techniques suitable for e-commerce data, ranging from Tree-based models (XGBoost/LightGBM) to Deep Learning architectures.
3. AI Engineering & Deployment (Software Focus)
- Production-First Mindset:Write clean, modular, and maintainable Python code tailored for production environments.
- Build and maintainAPI services(FastAPI/Flask) to serve models with low latency and high reliability.
- Collaborate with the Platform team to containerize models (Docker) and integrate them into the cloud infrastructure (Azure/Kubernetes).
- Implement MLOps best practices: Experiment tracking, model versioning, and automated testing.
Skills & Qualifications
Must-Haves:
- Experience:3-5+ years in AI/Data Science, with a proven track record of deploying models to production.
- Core ML/DL:Strong grasp of machine learning algorithms and deep learning architectures. Experience with frameworks likePyTorch, TensorFlow, Scikit-learn, or XGBoost.
- GenAI Proficiency:Hands-on experience building applications with LLMs, RAG architectures, and Vector Databases.
- Strong Software Engineering Foundation:
- Proficiency in Python and software design patterns.
- Experience building APIs (REST/gRPC) to expose AI services.
- Familiarity with Git, Code Review processes, and CI/CD basics.
- Problem Solving:Ability to translate business requirements (e.g., increase sales) into technical AI solutions.
Nice-to-Have (Priority given):
- Experience withMLOps tools(MLflow, Airflow, Kubernetes).
- Knowledge ofCloud Platforms(Azure is preferred).
- Background in E-commerce or Retail tech domains (Search, Pricing, Recommendations).
- Familiarity with other languages like Go, Java, or C++ (demonstrates strong engineering capability).
