Senior MLOps Engineer

At Graylight Imaging, the focus is on developing technologies for the medical field, especially analysing medical imaging studies and building machine learning algorithms for cardiology. The team contributes to solving unprecedented problems aimed at improving health and lives. The company conducts commercial projects alongside its own R&D.

• A technical college degree (PhD in computer science, statistics, or mathematics is a plus)
• At least 3 years of experience in machine learning
• Experience working with AWS services (AWS Batch, CloudWatch, SageMaker, S3)
• Experience with MLOps tasks including Amazon SageMaker, MLFlow, Weights & Biases; creating experiment hierarchies, parameter and repository tracking, building pipelines for preprocessing, training, and inference
• Optimising pipelines using GPU offload
• Developing computational methods like signal filtering and time and frequency domain analysis
• Very good knowledge of data visualisation, exploration, and analysis techniques for numerical and image data (3D)
• Knowledge of statistics, algebra, and mathematical analysis including statistical tests and matrix calculus
• Knowledge of machine learning, particularly deep learning
• Very good knowledge of neural network architectures including CNN and UNet
• Good knowledge of Python
• Very good knowledge of image processing and analysis algorithms
• Ability to implement and verify literature methods related to machine learning
• Understanding advantages and disadvantages of machine learning algorithms and clear presentation of developed solutions
• Independence, proactivity, openness to change, communication skills, analytical thinking
• Ability to organise work and manage time effectively
• Very good knowledge of English (minimum C1 level)

• Designing and implementing systems that process medical data using machine learning methods
• Conducting experiments to test designed algorithms, particularly deep neural networks for image data from CT or MRI
• Processing and analysing digital signals and developing methods for drawing conclusions
• Validating and evaluating algorithms through all software development stages including certification as medical devices
• Creating project documentation including experimental reports
• Collaborating with software engineers on technical solutions
• Analysing business requirements and designing technical architecture
• Mentoring and providing technical oversight for machine learning engineers
• Collaborating on tasks with machine learning and software engineers
• Facilitating knowledge sharing and process optimisation within the team
• Representing the company at conferences and industry events
• Supporting sales and business processes through technical input for proposals and applications