Anywhere, Remote · Full time
Getting entangled with stacks of analytical tools that don’t play well together, stops you from doing what you do best. To grow your customer base and scale your revenue, you need to learn from your data and put those insights to action faster.
GrowthSimple helps you harness the power of your data to build actionable behavioral models, focus on your buyer’s entire journey, run campaigns faster and integrate your learnings back into your analytics systems without worrying about long lead times to cobble complex tools together. You’ll identify your opportunities earlier and act on them faster to significantly scale revenue.
Are you looking for an opportunity to work on a machine learning platform that aims to revolutionize business growth by optimizing Conversion, Up-Sell, Retention & Engagement.
The GrowthSimple CURE TM platform enables SaaS & Subscription e-commerce companies worldwide to do more with their data. We work with growth and marketing managers who have marketing levers and are ready to leverage their data more completely. This is a huge and growing market.
As an ML Engineer, you will work on our platform which handles the full end-to-end machine learning lifecycle including rapid prototyping, training, deployment, monitoring, and model maintenance. We have access to a wealth of data to train high precision models. You will work closely with our ML engineers, data scientists and product manager to further develop our capabilities.
Entrepreneurial attitude - self-starter
Experience bringing machine learning models into production.
Hands-on machine learning experience (supervised/unsupervised)
Fluency in Python with the ability to write readable, modular, production-quality code
Experience with ML platforms in the industry such as Kubeflow, AWS Sagemaker, TFX, MLFlow
Experience with deep learning (LSTM, CNN)
5+ years of experience with 2+ implementing ML models
Experience with scheduling and orchestration systems, such as Airflow or Luigi
Experience with log analytics tools such as Data Dog, Segment, Splunk and New Relic.