£90000 - £120000 per annum + Amazing additional benefits
about 1 year ago
This disruptive AI-first InsurTech startup has a phenomenal opportunity for an accomplished Deep Learning Engineer to join their stellar engineering team and work alongside a host of talented data scientists and engineers. With substantial seed funding and now working towards their Series A, they are continuing to grow at a fast pace and now need a Deep Learning Engineer with specific expertise in Computer Vision to make a huge impact within their current pipeline of projects.
The Deep Learning Engineer Role
Coming in as the Deep Learning Engineer, you will have a stellar opportunity to further hone your technical skills in a fast-paced startup environment.
Researching state-of-the-art deep learning literature, implementing and experimenting with key concepts and deep learning models, then applying them to computer vision problems and OCR
Liaising closely with the DevOps team to put the machine learning models into production
Working with the data science team to design and develop client data processing pipelines, including data ingestion, cleaning, information extraction, fraud detection model calibration etc.
Working closely with senior management and stakeholders to understand their needs and iterate on existing solutions
Writing clean, production-ready code
The Successful Deep Learning Engineer
If you have been working as a Data Scientist, Machine Learning Engineer, Deep Learning Engineer or Computer Vision Engineer for several years in a commercial setting, this could be a fantastic next step for you in your career within a high-growth startup and alongside a stellar team.
Desired Skills and Background of the Deep Learning Engineer:
PhD / MSc in a degree related to DS / ML or a STEM degree
Proficiency in Python as well as core ML libraries (e.g. PyTorch, Tensorflow, Keras)
Commercial experience developing end-to-end deep learning solutions
If successful, you will be offered a highly competitive salary paying between £90,000 and £120,000 depending on experience, alongside excellent company benefits and stock options.