Senior Machine Learning Engineer, Aignostics

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. PhD is a plus
• 4+ years of work experience in software development, machine learning or a related field
• Advanced programming skills in Python, with experience with other languages (e.g. C/C++, CUDA, Java, Rust) being a plus
• Good understanding of distributed systems and frameworks, parallel computing and scalability
• Experience with cloud platforms (GCP, AWS or Azure), familiarity with MLOps / DevOps best practices (incl. CI/CD, Docker, Kubernetes and observability)
• Dedicated to high coding standards and knowledgeable about best practices in development workflow
• Experience with Linux, version control and container technologies
• Data engineering skills, experience with working with large datasets
• Excellent problem-solving skills and the ability to work independently and as part of a team
• Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders

Desirable

• As a Senior Machine Learning Engineer (d/f/m) at Aignostics, you work hand in hand with our collaborators in academia and industry to push the state of the art of machine learning for digital pathology
• You will develop distributed software systems for machine learning applications that will help to improve cancer research and diagnostics
• Together with your colleagues you will take care of the machine learning software stack and thereby enable our teams to build medical grade quality and scalable machine learning models
• At Aignostics, we believe that fighting cancer is a job for people of all identities, backgrounds, and cultures
• Design, develop, deploy and maintain robust ML pipelines to make them usable, efficient and scalable
• Optimize and fine-tune data pipelines for production
• Engage in code reviews, upholding high standards for clean, reliable code
• Collaborate with cross-functional teams to understand business requirements and translate them into ML solutions
• Embrace learning new technologies, fostering innovation, and tackling diverse challenges. Contribute to the development of our ML infrastructure, pipelines, services, monitoring systems and codebase in general
• Work in an agile development environment and clearly communicate your results to the team
• Mentor and guide junior engineers, providing technical leadership and insights