You will get Build enterprise AI agents | Ex-Tencent, 58.com ML Architect
Project details
I am a senior AI Algorithm Architect with over 15 years of experience in leading tech firms like Tencent and 58.com. I specialize in building "Self-Evolving" AI Agents and high-performance Recommendation Systems that drive real business growth. What sets me apart is my ability to bridge the gap between cutting-edge LLM technology (RAG, Function Calling, Reflection) and complex industrial scenarios. Whether you need to automate your recruitment pipeline with intelligent Agents or optimize your platform's conversion rate through advanced ranking models like pepnet or Transformer-based sequence modeling, I deliver production-ready solutions backed by a proven track record of increasing key metrics like VV and conversion by double digits.
Machine Learning Tools
Apache Spark, Apache Spark MLlib, Azure Machine Learning, BERT, BigDL, ChatGPT, Databricks MLflow, fastText, GitHub Copilot, GPT-3, NumPy, Open Neural Network Exchange, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Scrapy, SQL, Stanford CoreNLP, TensorFlow, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$400
|
Standard
$1,800
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 21 days |
Number of Revisions | 1 | 3 | 5 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 0 | 1 | 2 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
About Milan
AI & Machine Learning | Algorithm Development, Adaptive Algorithm
Beijing, China - 2:56 am local time
Steps for completing your project
After purchasing the project, send requirements so Milan can start the project.
Delivery time starts when Milan receives requirements from you.
Milan works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: Requirement Analysis & Technical Feasibility
Deep dive into your business goals, data availability, and specific pain points to design a customized AI solution.
Step 2: Architecture Design & Prototype Development
Design the system architecture, including RAG workflows, Agent memory mechanisms, or multi-objective ranking pipelines.