Machine Learning Engineer Goal Examples
Need inspiration setting Machine Learning Engineer goals? Check out the examples below to get started.
See more Engineering goalsEnhance your technical skills
As someone in a multi-faceted role, you have to ensure that you’re constantly developing your skills while revisiting existing skills so that you don’t lose them.
Stay up-to-date with latest AI research
Machine learning is a rapidly evolving field that’s always publishing new research. It’s important that you stay on top of this so that you don’t fall behind.
Ensure high code quality through automated unit and functional testing
As a high-paced engineering team, it’s important that we don’t lose out on quality as we scale. Make the effort to ensure that we’re maintaining our high standards as we push out new code.
Optimize existing pipelines
As our company begins to take on machine learning challenges, there will always be areas in which we can improve the quality of our pipelines. These can seem large and daunting, but breaking them up into small and measurable tasks will keep us moving in the right direction.
Looking to hit goals? 🙋♀️
Need a system that helps you stay on track to the goals you do set?
Let's face it
Effective teams hit goals 🎯
Align your team by setting collaborative goals that you can easily measure, track, and keep top of mind. Become a high-performance team with Hypercontext goals.