Python Ai

Description:

Network Ninja’s 3 enterprise products support 1M+ users across 500+ clients, and many of our clients have decades of data to mine for insights. The overall intent is to improve outcomes for our clients (and their clients), in addition to quality of life improvements for all roles at the company.

We have a handful of pilot and MVP AI/ML projects in flight, and are confident the recent, and upcoming, changes in market offerings will change our company dramatically in the near future.

If you’re interested so far, please read the rest of the req in its entirety, and follow the instructions contained within to apply. There will be 1 screening interview with senior management, and then 1 technical interview with members of the Infrastructure team. We move methodically, and quickly, and you probably do, too, so this can be an efficient process.

Responsibilities, Requirements, and Job Concepts

Requirements are based on our findings so far, and because of that they are somewhat flexible. Candidates need to be technology enthusiasts and evangelists, and have a demonstrated track record of learning then building/iterating rapidly.

• Evangelize AI/ML/NLP.

Python, OpenAI, Hugging Face, and AWS

Our custom frameworks are written in PHP and JavaScript, and a majority of our developers are PHP specialists - not Python developers. While this is exciting to some, it is concerning for others. Candidates should have the ability to advocate for, train others on, and implement new technologies.

A likely path forward is building APIs on AWS and Hugging Face for product teams to leverage.

• AWS experience required, specifically Lambda and SageMaker.
• Understand how to use OpenAI API, including function calling.
• Have familiarity with Hugging Face Inference Endpoints.

Transform and Analyze - both internal and client data

To support our clients, and internal operations, we’ve been using a variety of tools to prepare data for processing, and extract meaning from that data. We want to do more, and in a more focused manner. Our employees need, in some cases, toolkits, in other cases actual data crunching performed for them by the nascent AI/ML team.

It is likely these tools will heavily leverage the following, all desired but not required:

• Pandas, NumPy, and SciPy
• Scikit-learn, TensorFlow, or PyTorch