Machine Learning Engineer

Responsibilities:

1. Develop fast and energy efficient vision-based machine learning pipelines for our clients

2. Develop and maintain synthetic data generation systems

3. Develop and maintain training loops for vision-based deep learning models in Python

4. Efficiently implement machine learning algorithms on edge-based hardware in C++

Qualifications and Experience:

1. Expertise with PyTorch and with MLOps software stack

2. Familiarity with Computer Vision – classical and deep learning-based algorithms

3. HE degree in an analytical STEM field

4. Provable prior experience using ML systems (extensive university projects are acceptable)

5. Good software development and research skills

What we will assess you on:

1. Your interesting projects producing or using cutting edge ML techniques

2. Your excellent software development techniques

3. A demonstration of your understanding of the latest techniques in computer vision and ML

Bonus:

1. Knowledge of cuda kernels and GPU architecture would be great (extra bonus for knowledge of TensorRT and Triton kernels)

2. Experience with implementing ML applications on low power edge hardware is a plus

3. Knowledge of ROS2/Gazebo/Nvidia Isaac Sim and robotics would help

4. Experience training highly quantised models (int8 and below)

5. Experience synthesising data for any ML task (we’re particularly interested in vision but would be happy to hear any)

6. A deep understanding of C++ certainly helps our team and would give you an edge (extra bonus for using LibTorch 2.5+)

Provide us with:

1. A code repository or Jupyter notebook that you’re most proud of making – please make it self-contained, OR

2. A written document in your own words about what you think is the next best thing in ML and why.