Senior Machine Learning Engineer Job at Aignostics (Berlin)

Senior Machine Learning Engineer

Aignostics

Location:
Germany , Berlin

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

As a Senior Machine Learning Engineer 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.

Job Responsibility:

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

Requirements:

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

Nice to have:

Experience with deploying models into production
Experience with Google Kubernetes Engine, Ray distributed computing framework and Prefect
Hands-on experience with machine learning and data science. Proven experience with ML framework, such as Tensorflow, PyTorch or scikit-learn
Experience with working on biomedical data (especially working with image data)
Experience with software development in regulated environments, specifically considering Information Security criteria under ISO 27001

What we offer:

Join a purpose-driven startup: We are working collectively to fight cancer and improve patient outcomes
Cutting-edge AI research and development, with involvement of Charité, TU Berlin and our other partners
Work with a welcoming, diverse and highly international team of colleagues
Opportunity to take responsibility and grow your role within the startup
Expand your skills by benefitting from our Learning & Development yearly budget of 1,000€ (plus 2 L&D days), language classes and internal development programs
Mentoring program, you’ll learn from great experts
Flexible working hours and teleworking policy
Enjoy your well-deserved time off within our 30 paid vacations days per year
We are family & pet friendly and support flexible parental leave options
Pick a subsidized membership of your choice among public transport sports and well-being
Enjoy our social gatherings, lunches, and off-site events for a fun and inclusive work environment
Optional company pension scheme

Additional Information:

Job Posted:
December 16, 2025

Employment Type:

Fulltime

Work Type:

Hybrid work

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