What do I do at Relevance AI?
My name is Chakaveh Saedi, I’m a Machine Learning Engineer and Data Scientist. I lead the Education team that sits within Customer Success at Relevance AI.
Customer success has a close connection with other teams such as product and front-end. Our goal is to provide our customers with optimal functionalities and resources throughout their experience with Relevance AI’s platform. I am passionate about applying what I have learned in academia and my work experiences to real-world problems.
My responsibilities vary from working on POCs, designing understandable and easy-to-follow documentation & presentations, platform testing and improvement suggestions, and working on the codebase.
My career’s journey so far
I have been working in Artificial Intelligence field for over 10 years now in both academia and industry settings.
I started as a researcher, then gradually moved towards industry through projects and my different work experience. A few months ago, I submitted my PhD thesis around the time I joined Relevance AI.
Before Relevance AI, I had worked as a data scientist and machine learning engineer at AI companies such as Sypht in Sydney and NLX research group in University of Lisbon, Portugal.
I decided to join Relevance AI as I found what they do extremely interesting and a huge indication of bringing research into real-world problems.
What I’m most excited about
I’m excited about employing AI, machine learning & data science for offering creative solutions to complex and interesting problems that many companies are dealing with. I look forward to our coming product and feature launches, focusing on providing the best possible experience to our customers.
What my average day at Relevance AI looks like
My typical day at Relevance AI:
- On any given day, I am usually working on two major tasks. If coding, typically I work with Python.
- I start my days by focusing on high-priority projects that need more time and deeper thoughts.
- The most recent one is a demo for a client looking for clustering through vectors.
- Building demos are an interesting process. First, I analyse the data and decide what the most informative fields are. Then, using state of the art neural models, the sample data that our clients provide us are vectorized and the best combination of data fields, models and parameters is decided by running various experiments.
- Another ongoing project in the team is modification and testing our documentation and guides to be always fully compatible with the latest updates to the SDK.
- I might have different quick or rather longer calls with different team-mates to brainstorm and decide how to proceed with a specific task.
- And when time allows, I try to work on some side experiments with vectors and different models. After all, RelevanceAI is an experimental platform!
- Currently, I am running an experiment on finding similarities using Siamese neural network structure. For this, I am using audio files which can be used for music recommendations or similar tasks.
What I do when I’m not at work
I am into nature and try to live an active lifestyle. So, when I am not at work and when the weather allows, I am most likely hiking in NSW’s beautiful nature. Otherwise, swimming and reading are on top of my list.