Machine Learning Engineer for Model Deployment and Innovation
Vor 4 Tagen
Are you a seasoned Machine Learning expert looking to take your skills to the next level at Flink?
About the RoleWe are seeking an experienced Senior Machine Learning Ops Engineer to join our team in Berlin. As a key member of our engineering department, you will play a crucial role in shaping the future of our Data Products.
Job Responsibilities- Create scalable systems that automate ML model lifecycle management, including training, testing, monitoring, and deployment.
- Develop and maintain internal services delivering real-time predictions for our recommendations engines, impacting consumer-facing applications.
- Lead the development and maintenance of our Data Products, collaborating with cross-functional teams and stakeholders.
- Closely work with Data, Platform, and other organisational teams to implement optimal solutions.
- At least 4 years of experience designing, developing, and deploying Machine Learning products.
- Previous experience with architectural input into Data/Machine Learning product design and build.
- Proficiency in Python programming and familiarity with commonly used libraries.
- Able to provision and configure infrastructure for ML/Data products, as well as deploy and scale them in public cloud environments.
- Experience with ML platforms (MLflow, Kserve, Feast).
- Comfortable navigating and translating Data Scientist needs into practical solutions.
- Good grasp of CI/CD pipelines and IaC tools.
- Open-minded personality, comfortable working in Agile environments.
- €80,000 - €110,000 annual salary, depending on experience.
- 26 days of vacation, +1 day per year up to a maximum of 30 days.
- €1000 annual L&D budget and individual coaching options.
- Mobility budget of €30 per month.
- Urban Sports Club membership discount.
- Company pension options.
- Unlimited access to MyAcademy e-learning platform.
- Discounts with Corporate Benefits and Future Bens.
- Dog-friendly office in Berlin's city centre.
Flink is committed to evaluating applicants based on their skills, regardless of age, gender identity, ethnicity, sexual orientation, disability status, or religion.
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