What are the responsibilities and job description for the Machine Learning Engineer position at IRL?
IRL’s AI Team is looking for a machine learning engineer to help us build end-to-end machine learning solutions for millions of users.
In this position, you will work closely with product teams to convert their wildest ideas into reality with AI.
If you're interested in developing highly scalable machine learning systems from the ground up, let's chat!
Day-to-day responsibilities include:
- Talk to product teams to identify machine learning applications
- Design overall machine learning system for each application
- Collaborate with data engineers to collect data
- Design features and train machine learning models
- Deploy machine learning models in a scalable fashion
You should apply for this role if you have the following qualifications:
- Excellent software engineering skills
- Knowledgeable about machine learning techniques (overfitting vs underfitting, tradeoffs between different models...)
- Experience in one of the major machine learning packages (PyTorch, Tensorflow, Keras…)
- Proficient in Python
- Experience in AWS core services
The focus and potential success of this role:
Recommendation focus:
Success after 3 months would include objectives like:
- Design and deploy a machine learning model for recommendation.
Success after 6 months would include objectives like:
- Design and deploy an automated and maintainable machine learning system that regularly re-trains on new data for recommendation.
Success after 12 months would include objectives like:
- Show significant improvement in business metrics with deployed machine learning systems, such as 30% relative increase in click-through rate.
Chat focus:
Success after 3 months would include objectives like:
- Deploy and deploy a machine learning model for chat, such as spam detection.
Success after 6 months would include objectives like:
- Design and deploy an automated and maintainable machine learning system that regularly re-trains on new data.
Success after 12 months would include objectives like:
- Show significant improvement in business metrics with deployed machine learning systems, such as 30% decrease in spam rate.
Content focus:
Success after 3 months would include objectives like:
- Deploy a machine learning model to scrape contents to create events and groups.
Success after 6 months would include objectives like:
- Design and deploy an automated and maintainable machine learning system that regularly re-trains on new data.
Success after 12 months would include objectives like:
- Show significant improvement in business metrics with deployed machine learning systems, such as 30% relative increase in the number of groups users joined.