If you are looking for a place to grow your career and impact millions of people, MoMo might be just the right place for you.
What you will do
ML platform development. We want to make the data science and machine learning workflows efficient and robust to operate, manage, and scale for our data scientists. As the result, we are investing in building a best- in- class ML platform to serve their needs. You are in charge of taking the status quo, researching the state of the art, helping define the roadmap and executing.
Collaboration with data scientists. Our team works on a wide range of problems such as search and discovery, recommender systems, communication and promotion targeting, ad serving and ranking, credit scoring, fraud detection. You will work closely with our data scientists to understand their requirements and challenges, and provide them with tailored solutions to optimize their workflows
Resource monitoring and optimization. Monitoring the performance of the ML platform and proactively identifying areas for optimization. This includes analyzing system performance, ensuring low latency, and optimizing cloud resource consumption for cost- effective operations.
Implementing MLOps practices. Hands- on work to build and maintain tools for feature engineering and exploration, maintain CI/CD pipelines and Kubernetes deployments, and develop a framework for testing and monitoring ML systems.
Leadership. Leading and mentoring team members, delivering feedback and guidance to help them grow.
This will be a challenging but rewarding role as you can see your work directly impact the ways of working of fellow data scientists while delivering business values at the same time.
What you will need
ML platform development. We want to make the data science and machine learning workflows efficient and robust to operate, manage, and scale for our data scientists. As the result, we are investing in building a best- in- class ML platform to serve their needs. You are in charge of taking the status quo, researching the state of the art, helping define the roadmap and executing.
Implementing MLOps practices. Hands- on work to build and maintain tools for feature engineering and exploration, maintain CI/CD pipelines and Kubernetes deployments, and develop a framework for testing and monitoring ML systems.
Collaboration with data scientists. Our team works on a wide range of problems such as search and discovery, recommender systems, communication and promotion targeting, ad serving and ranking, credit scoring, fraud detection. You will work closely with our data scientists to understand their requirements and challenges, and provide them with tailored solutions to optimize their workflows
Resource monitoring and optimization. Monitoring the performance of the ML platform and proactively identifying areas for optimization. This includes analyzing system performance, ensuring low latency, and optimizing cloud resource consumption for cost- effective operations.
Leadership. Leading and mentoring team members, delivering feedback and guidance to help them grow.
This will be a challenging but rewarding role as you can see your work directly impact the ways of working of fellow data scientists while delivering business values at the same time.
