Key skills
AWSAzureCloudDistributed SystemsDockerGoogle Cloud PlatformJavaKubernetesLinuxPythonRustC++CMachine LearningMLMLOpsData EngineeringGCPGoogle CloudVersion ControlAgileCI/CDLeadershipMentoringCommunication
About this role
Role Overview
- 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 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.
Tech Stack
- AWS
- Azure
- Cloud
- Distributed Systems
- Docker
- Google Cloud Platform
- Java
- Kubernetes
- Linux
- Python
- Rust
Benefits
- 30 paid vacation days per year
- Flexible working hours and teleworking policy
- Learning & Development yearly budget of 1,000€ (plus 2 L&D days)
- Mentoring program
- Family & pet friendly
- Flexible parental leave options
- Subsidized membership among public transport, sports and well-being (in Germany)