Text copied to clipboard!
Title
Text copied to clipboard!Machine Learning Engineer
Description
Text copied to clipboard!
We are looking for a Machine Learning Engineer to join our team. The ideal candidate will have industry experience working on a range of different machine learning disciplines, e.g. anomaly detection, payment fraud, fraud detection, search ranking, text/sentiment classification, spam detection and others. The successful candidate will be responsible for designing machine learning systems, running machine learning tests and experiments, implementing appropriate ML algorithms, and applying machine learning algorithms and libraries. You will be part of a team that values collaboration, innovation and the ability to work on groundbreaking technologies. You will work closely with data scientists, data engineers and other stakeholders to turn data into critical information used to make sound business decisions.
Responsibilities
Text copied to clipboard!- Design machine learning systems.
- Research and implement appropriate ML algorithms and tools.
- Develop machine learning applications according to requirements.
- Select appropriate datasets and data representation methods.
- Run machine learning tests and experiments.
- Perform statistical analysis and fine-tuning using test results.
- Train and retrain systems when necessary.
- Extend existing ML libraries and frameworks.
- Keep abreast of developments in the field.
- Collaborate with data scientists and engineers on projects.
Requirements
Text copied to clipboard!- Proven experience as a Machine Learning Engineer or similar role.
- Understanding of data structures, data modeling and software architecture.
- Deep knowledge of math, probability, statistics and algorithms.
- Ability to write robust code in Python, Java and R.
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).
- Excellent communication skills.
- Ability to work in a team.
- Outstanding analytical and problem-solving skills.
- BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus.
- Experience with cloud services (GCP, AWS, Azure) is a plus.
Potential interview questions
Text copied to clipboard!- What machine learning frameworks and libraries are you familiar with?
- Can you describe a machine learning project you've worked on?
- How do you handle missing or corrupted data in a dataset?
- Can you explain the difference between L1 and L2 regularization?
- What is your process for fine-tuning a machine learning model?