Abingdon Health Hiring for Software Engineer – Deep Learning Job at London, England Full Time

Abingdon Health is a UK-based developer and manufacturer of lateral flow tests and smartphone reader solutions. Abingdon Health offers development and manufacturing services for customers looking to develop new assays or looking to transfer existing laboratory-based assays to a lateral flow format. Abingdon takes projects from initial concept through to routine and large-scale manufacturing.

Abingdon Health is headquartered in York, England.

The AppDx® platform at Abingdon Health brings together a tight-knit and cross-functional R&D team of technology specialists, with expertise in software development, machine learning, quality assurance, and product innovation. The team is seeking a deep learning software engineer on a contract basis to work on the company’s proprietary technology and algorithms as part of a multi-year innovation project. The team’s goal is to establish the gold standard in diagnostic accuracy for the mobile reader market.

To date, the team have experienced several commercial wins using their patented hybrid signal processing and machine learning technology. They are now working on a system incorporating deep learning in an end-to-end fashion as part of the next generation of AppDx® lateral flow software. In addition to developing core algorithms, there is significant opportunity to commercialize AppDx® by bringing models into production in partnership with a handful of key customers. As such, any exposure to the machine learning production cycle is especially desired.

Primary Duties and Responsibilities:

· Design and implement deep learning and image processing algorithms in Python.

· Manage/process image data and create/annotate high-quality training datasets.

· Train/tune/evaluate models and deploy trained models to a smartphone platform for on-device inference.

· Design and build infrastructure for model monitoring/maintenance.

· Write and maintain excellent technical and software documentation.

· Write unit tests to run in continuous integration pipelines.

· Work within an Agile software development process.

· Scope projects alongside key internal and external stakeholders.

Essential

· Undergraduate or master’s degree in Computer Science, Physics, Mathematics, or equivalent domains (undergraduate-level candidates must have 2+ years’ experience in an industrial or research environment).

· Excellent programming skills in Python.

· Experience working with deep learning frameworks such as TensorFlow/PyTorch.

· Strong understanding of deep learning and computer vision tasks.

· Strong understanding of convolutional neural networks (CNN).

· Experience working with large, modular Python projects and Jupyter notebooks.

· Knowledge of OOD/OOP, functional programming, and design patterns.

· Strong understanding of the Software Development Lifecycle.

· Experience working with image and numerical processing libraries such as Pillow/OpenCV and NumPy/SciPy.

· Demonstrated skills in the machine learning domain via projects or thesis.

· Demonstrated skills in implementing algorithms as end-to-end solutions.

· Proficiency with Microsoft® Word, Excel®, and Power Point®.

· Proficiency in English, both spoken and written.

· A proactive attitude and a desire to research problems and create solutions.

· High-level analytical thinking and the ability to communicate complex information clearly.

· Ability to work within a multidisciplinary team of developers, scientists, and engineers.

Desired or Bonus Skills

· Knowledge of modern CNN architectures (e.g., ResNet/MobileNet, etc.).

· Knowledge of frameworks for on-device inference (e.g., TensorFlow Lite).

· Experience bringing machine learning models to users.

Job Types: Full-time, Permanent

Salary: £25,000.00-£45,000.00 per year

Benefits:

• Flexible schedule
• Work from home

Schedule:

• 8 hour shift
• Monday to Friday

Application question(s):

• Can you confirm you meet the Essential requirements of the role?

Education:

• Bachelor’s (preferred)