- Coordinating with other team members.
- Creating and managing the AI development process and overall infrastructure of a product.
- Conducting statistical analysis and interpreting the results to guide an organization’s decision-making process.
- Automating important infrastructure for the data science team.
- Developing infrastructures for data transformation and ingestion.
- Building AI models that make predictions based on large quantities of data.
- Explaining the usefulness of the AI models they create to a wide range of individuals within the organization, including collaborators and product managers.
- Transforming the machine learning models into APIs to interact with other applications.
- Experience as an Machine Learning and Artificial Intelligence.
- Experience with Neural Networks.
- Experience with Natural Language Processing.
- Experience with Robotics, Autonomous Driving Technology.
- Experience with Visual Image Recognition.
- Experience with Spark and Big Data Technologies.
- Experience with Programming languages like Python, Java, Scala, R, and C++.
- Experience with Data Science, Statistics and probability, Algorithms and Frameworks.
- Experience with Data Engineering, Exploratory data analysis.
- Ability to Convert the machine learning models into application program interfaces (APIs) so that other applications can use it.
- Ability to Build AI models from scratch and help the different components of the organization (such as product managers and stakeholders) understand what results they gain from the model.
- Ability to Build data ingestion and data transformation infrastructure.
- Ability to Automate the infrastructure that the data science team uses.
- Ability to Perform statistical analysis and tune the results so that the organization can make better-informed decisions.
- Ability toSet up and manage AI development and product infrastructure.
- Be a good team player, as coordinating with others is a must”.
Further information: [email protected]