Our machine learning engineers are responsible for creating innovative approaches to harness the power of data to solve real-world problems. They are fluent in programming and have superior analytical skills. They must have a very strong background in artificial intelligence and machine learning; both in theory and application. We expect our ML engineers to not only be able to train and create machine learning models, but to understand at an intuitive level why some techniques work better than others.
- Formulate real-world problems into AI/ML problems.
- Research information to gain deeper understanding about the given problem and the appropriate solutions for solving it (may involve reading academic papers).
- Write programs to process, sanitize, clean, manipulate data, which may be unstructured
- Build a database/corpus of relevant data for the purpose of machine learning.
- Create machine learning algorithms using a combination of existing libraries/frameworks and own code.
- Run experiments based on various solutions, analyze results, and produce/present reports to the team.
- Productionize AI/ML systems in order to solve the assigned problems.
Preferred requirements & competencies
- Good understanding of the foundation of artificial intelligence and machine learning both in theory and application
- Experience in developing and deploying Machine Learning models
- Familiar with machine learning frameworks such as Tensorflow or PyTorch
- Can write complex programs fluently and efficiently
- Strong analytical skills. Can investigate and fix models’ performance issues
What We Value
- People with strong logic skills who value evidence over emotions
- People who not only solve problems, but also understand their solutions
- Team members who have a high sense of ownership in their work
- Team players who are always looking for ways to help out others
- People who are proactive and take initiative