Job description
Job Summary:
- As a Machine learning engineer who will develop self-running AI software to automate predictive models for recommended searches for our AI Engine. Who will design machine learning systems, apply algorithms to generate accurate predictions, and resolve data set problems.
What you'll do
- Partner with data scientist working on discovery, prototypes and pilot. Focus on experiment tracking.
- Partner with data scientist & ML engineers to design, develop, and deploy deep & machine learning applications using complex high dimensional features that run efficiently in cloud.
- Design, build, and maintain the core machine learning capabilities, services and platforms.
- Design and implement end-to-end machine learning pipelines accounting for the variability in data sources and collection policies, data analysis and feature extraction methodologies, modelling frameworks and serving infrastructure.
- Help drive optimization, testing, and tooling to improve quality (unit tests).
- Implement integrated monitoring of model performance for reliability and maintenance.
- Monitor model performance, working with data scientists assessing models performance, bias & fairness.
- Work with a wide range of systems, processes and technologies to own and solve problems.
- Continuously improve ML processes, tools and standards.
Work Experience
What you've done
- 3+ Experience deploying production-grade AI applications.
- Solid technical knowledge of python, data structure, flask or fastapi.
- Strong technical knowledge of classical ML approaches as well as novel deep learning methods.
- Proficiency with deep learning frameworks such as TensorFlow/Keras or PyTorch (Basic Understanding is must) as well as packages for machine learning such as scikit-learn and pandas.
- 3+ years' experience in ETL and/or data wrangling techniques.
- Fluent with Azure cloud services, AWS
- Fluent in git (version control), Docker, Jenkins.
- Fluent with design and management of