Responsibilities

Your Impact:

• Build distributed, real-time, high-volume data & ML pipelines and work together with others to enable high-scale ML applications
• Work with ML frameworks, Feature Stores, Data pipelines
• Join a high-performance team solving hard problems the right way focused on customer value
• Own service built from the ground up, learn, have an impact

Qualifications

Your Experience:

• Bachelor’s degree with 5 years of industry experience, or Master’s degree with 3 years of industry experience
• 2 years of experience in building machine learning applications in production at scale
• Experience in data science & machine learning in multiple domains), both statistical and deep learning (with Time series analysis & NLP), with experience developing and running ML models at scale in production
• Experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, Mechanism Design, etc.)
• Background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
• Hands-on experience with statistical packages, ML libraries (e.g. R, Python scikit learn, Spark MLlib, etc.), and ML frameworks such as TensorFlow and PyTorch
• Experience with public cloud (AWS, GCP, etc) ML offerings and driving their adoption
• Familiarity with ML model development frameworks, ML orchestration and pipelines with experience (e.g., Airflow, Kubeflow or MLFlow)
• Excellent oral and written communication skills