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
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.
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.
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.
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
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
Strong product ownership. You take a high responsibility for what you build and keep a high bar for product quality.
Have experience with tech- leading or management. You enjoy helping others grow with you.
5+ years of hands- on industrial experience with Big Data and Machine Learning. You have solid understanding as well as hands- on experience of building complex ML systems and applying MLOps practices.
Experience with cloud services like GCP, AWS is highly preferred.
Educational background. You possess a Bachelor’s or Master’s degree in Computer Science or a related field with a strong focus on machine learning. Higher degree or additional training is a plus.
Have experience in applying Machine Learning for user problems such as product and service search and recommendation, marketing and promotion personalization. Proficient with big data processing techniques for feature engineering and model training. Experience with building high- throughput and low- latency systems is a plus.
Strong communication skills. This position requires working closely with data scientists, MLEs from different domains, management and other tech teams.
