Machine Learning Engineer in Python (Full-time)

We are looking for Machine Learning engineers to develop AI solutions.

This is a full-time position in an international team, starting at XXX USD / month.

We offer:

- Flexible work hours
- 4 weeks of paid leave
- Holidays off

Skills we are looking for:

- Experience solving problems with Machine Learning
- Experience designing, training, and deploying deep learning applications
- Knowledge of existing deep learning frameworks, such as Tensorflow, Pytorch, or JAX
- Good overview over existing techniques in deep learning to tackle various modalities of data (images, text, structured data, etc.)
- Independent mindset

If you are interested, reach out to us! Please tell us about yourself, your personality, and about your past experience, and list your proficiency in each of the list items above. Also show us work that you've done in the past and of which you are particularly proud of by answering the following questions below:

About You
- Tell me about yourself?
- Why do you want to be a machine learning engineer?
- What are your salary expectations as a machine learning engineer?
- How does this work fit into your life?
- Where do you see yourself in five years' time?
- Why should we hire you?

Experience
- How long have you been in the industry?
- Tell me a brief overview of your past work?
- Show me a particular piece of work you're proud of. What's the story behind it?
- Tell me a time when you worked as part of a team to solve a complex task?

Strengths and Weaknesses
- What are your strengths?
- What are your weaknesses?

Role-specific questions
- Explain the terms AI, ML and Deep Learning?
- What’s your favorite ML algorithm, and can you explain it to me?
- What is the difference between supervised and unsupervised machine learning?
- What’s the trade-off between bias and variance?
- What is deep learning, and how does it contrast with other machine learning algorithms?
- What’s the difference between a generative and discriminative model?
- How would you handle an imbalanced dataset?
- How do you ensure you’re not overfitting with a model?