Senior Machine Learning Engineer (d/f/m)
Berlin
Aignostics GmbH
Aignostics turns complex biomedical data into transformative insights for biopharma companies through development of AI-powered precision medicine for pathology throughout the drug development pipeline from target identification, to...Why us?
We believe that AI has the potential to revolutionize how cancer and other complex diseases are diagnosed and treated. We also believe that AI is a tool, not an identity – without access to high quality data and a scientifically rigorous, transparent approach to model development, AI is just a buzzword. That’s where we come in.
Aignostics is a spin-off from one of Europe's largest and most prestigious university hospitals (Charité), with employees in Berlin and New York. We have received over $50M in funding from leading investors and are a growing team of over 100 interdisciplinary professionals. We work with academic partners as well as leading global life sciences companies.
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. We value and celebrate diversity and inclusion and are committed to offering equal employment and promotion opportunities for all applicants and employees. Applicants will be considered regardless of their age, disability, ethnicity, race, gender identity or expression, sexual orientation, religion, etc. We thrive through collaboration and believe the more inclusive we are, the better our work will be.
Please note that this position is intended for software engineers. For a data scientist / machine learning / deep learning position please check out our Data Scientist opening.
Where your expertise is needed
- 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.
What we are looking for
- 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.
- 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
Our offer
- Join a purpose-driven startup: We are working collectively to fight cancer and improve patient outcomes. Come help us make a difference!
- 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 28 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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AWS Azure CI/CD Computer Science CUDA Data pipelines Deep Learning DevOps Distributed Systems Docker Engineering GCP ISO 27001 Java Kubernetes Linux Machine Learning Mathematics ML infrastructure ML models MLOps PhD Pipelines Python PyTorch Research Rust Scikit-learn Security TensorFlow
Perks/benefits: Career development Flex hours Flex vacation Medical leave Parental leave Startup environment Team events
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.