Machine Learning Engineer for Influencer Outreach & Automation Tool
Budget: -
HOURLY / PART_TIME
⭐ 0.00 (0)
Pakistan
machine-learning, machine-learning-model, python, python-script, requests, data-analysis, dax-language, deep-learning, deep-learning-model, computer-vision, neural-networks, artificial-neural-networks, data-visualization
Preferred qualifications
- Experience: Intermediate
Machine Learning Engineer | AI-Powered Influencer Outreach & Automation Tool
I am looking for an experienced Machine Learning Engineer / AI Engineer to help build an AI-powered Influencer Outreach & Management Platform for influencer marketing.
The goal is to create a software tool that can help manage the complete influencer outreach process — from finding and analyzing influencers to influencer scoring, personalized outreach, follow-ups, campaign management, and performance analytics.
This is planned as a long-term project, starting with an MVP and expanding into advanced AI/ML features.
What I Want to Build
The platform should eventually include:
Influencer discovery and database
Influencer search and advanced filtering
Influencer profile management
Influencer niche and audience analysis
Influencer scoring and ranking
Influencer-product matching
AI-powered influencer recommendations
Outreach campaign management
Personalized AI-generated outreach messages
Follow-up management
Contact and conversation tracking
Influencer CRM
Campaign analytics
Influencer performance analytics
Automated workflows
AI / Machine Learning
AI and Machine Learning will be a core part of the platform.
I want to explore features such as:
Influencer recommendation systems
Influencer scoring and ranking
Influencer-product matching
Audience/niche classification
Engagement-quality analysis
Predictive campaign performance
AI-powered search
Personalized outreach generation
Response/interest prediction
Learning from historical campaign data
I am open to your recommendations regarding the best ML models, AI architecture, APIs, databases, and technology stack.
Required Experience
You should have strong experience with:
Machine Learning
Artificial Intelligence
Python
Generative AI / LLMs
NLP
Recommendation Systems
Predictive Modeling
Data Analysis
API Integration
REST APIs
Backend Development
Database Design
SaaS Development
Experience with OpenAI API, embeddings, vector databases, RAG, AI agents, or automation workflows is a strong advantage.
Experience with influencer marketing, social media analytics, marketing automation, CRM, lead generation, or SaaS platforms is highly preferred.
MVP
I want to start with a practical MVP rather than building everything at once.
The initial version may include:
Influencer database
Search and filtering
Influencer profiles
Influencer scoring
Campaign management
Outreach management
AI-assisted personalized messages
Follow-up tracking
Basic analytics
Admin dashboard
Required API integrations
The exact MVP scope will be finalized with the selected developer.
Important
I am not looking for a basic CRM or simple web developer.
The long-term vision is an intelligent platform that can help answer:
Who should I contact?
Why is this influencer a good fit?
How should I approach them?
When should I follow up?
Which influencers are most likely to perform well?
The system should use AI, Machine Learning, data, and automation to make influencer outreach more efficient and data-driven.
What to Include in Your Proposal
Please answer these questions:
Have you built any AI/ML SaaS, recommendation, automation, CRM, or marketing platforms?
What experience do you have with Machine Learning and recommendation/ranking systems?
What AI/LLM technologies have you worked with?
How would you approach influencer scoring and recommendation?
What technology stack would you recommend?
What would you include in the first MVP?
What is your estimated timeline and budget?
How many hours per week are you available?
Please do not send a generic proposal.
Start your proposal by explaining briefly how you would build an AI-powered influencer scoring and recommendation system.
This is intended to be a long-term collaboration if the initial MVP is successful.
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