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Are you interested in working with a team that is responsible for machine learning services from the moment they are ideated to the moment they are an existing fact, in a product that scales? If so, keep reading…
What this role is:
You will be working closely with both the machine learning research team and the data operations team to build tools for generating and annotating data. You will help define the data needs for projects and find this data either from public or in-house sources.
What this role is not:
You will not be a simple programmer who is given detailed specifications and forced to write code that others want you to. You won’t have all the technical decisions made for you. We want real software engineers here – people who care about doing it right the first time.
This role is also not a researcher role in a ML research team, but a role that supports existing researchers and the DataOps (annotation) teams in tasks that need automation development.
What you will bring to the table:
You should be a lifelong learner who can work well within a team. You should be a strong problem solver who can debug complex customer situations one day and build out new scalable code the next. You should be detail-oriented, be smart, and get things done.
Some details about what you will do day to day:
Help expand existing services and datasets to new languages.
Add data to existing ML models training scripts and services.
Build and use tools that automatically annotate data, using external or internal ML models.
Build tools to scrape the internet for pin-pointed data needs.
Use LLMs to generate synthetic data.
Improve and clean existing datasets using automated tools.
Create tools for continuously and automatically checking the quality of data.
BS in Computer Science or Software Engineering (or strong relevant experience)
5+ years of experience in Software Engineering with the majority of that working in some type of backend code.
Experience with the Linux operating systems.
Experience using REST APIs.
Experience with python and bash scripting.
Experience with UI (Vue/React) an advantage.
If a Genesys employee referred you, please use the link they sent you to apply.
Every year, Genesys orchestrates billions of remarkable customer experiences for organizations in more than 100 countries. Through the power of our cloud, digital and AI technologies, organizations can realize Experience as a Service™ our vision for empathetic customer experiences at scale. With Genesys, organizations have the power to deliver proactive, predictive, and hyper personalized experiences to deepen their customer connection across every marketing, sales, and service moment on any channel, while also improving employee productivity and engagement. By transforming back-office technology to a modern revenue velocity engine Genesys enables true intimacy at scale to foster customer trust and loyalty. Visit www.genesys.com.
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