Cherry Ventures is supporting our portfolio with this hire

Data Engineer MLOps Focus

Berlin based m/f/d fulltime

What we do at Plato

Plato is building the digital backbone of the global trade economy. Starting with the $48T wholesale industry we empower the modern wholesaler to connect their people and data in a single analytics and workflow hub. By leveraging data science and AI we automate workflows and combat labor shortages making SMB wholesalers competitive with large corporations.

Why we do what we do

The future of wholesale is datadriven. Unlike popular opinion Industrial SMEs are ready to make the step to become more proactive in their processes but lack the technology to steer them to success. Our founders come from a wholesale family and gathered a rock star team of exBig Tech VC and toptier consulting companies to reshape the operations of this $48tn industry. Our initial product leverages cuttingedge data science to provide customized demand forecasts and product recommendations combined with intelligent workflow automation.

We are about to create categorydefining software. Our primary customers are Csuite executives within largescale wholesale and distribution businesses. We are committed to helping them enhance their decisionmaking processes and optimize their operations through the smart use of their data bringing their operations into the 21st century! But dont just hear it from us! We are supported by a list of toptier EU & US VCs advisors and angels providing insights from some of the best SME tech companies such as Miro Celonis Personio Workday Forto and Microsoft.

What were looking for

MLOps DataOps DevOps ModelOps

At Plato we are building a realtime data platform. As a member of our team you will play a pivotal role in developing and maintaining the infrastructure that powers our ML solutions.

A significant challenge we face is onboarding a large number of customers onto our platform where automation and repeatability are crucial for success. This role combines the best of data engineering with the demands of machine learning operations ensuring the seamless operation of data pipelines and ML models from development to production.

The ideal candidate is an innovative problemsolver who is passionate about both data engineering and MLOps. You will thrive in our dynamic startup environment wearing multiple hats when required to meet our evolving needs. Your ability to collaborate across teams automate processes and ensure repeatability will be key to driving our data and ML infrastructure forward.

What youd be working on

• Design develop and manage scalable and robust data pipelines that support machine learning models in production.
• Implement and maintain CI/CD pipelines for data and ML workflows ensuring smooth transitions from development to production.
• Automate the onboarding process for new customers ensuring scalability and repeatability across deployments.
• Collaborate with data scientists and AI Engineers to optimize and automate data processing and model deployment.
• Ensure the seamless integration of ML models with production environments enabling realtime and batch inference capabilities.
• Develop and maintain tools and frameworks for automated data management model retraining and monitoring.
• Utilize MLFlow for model tracking versioning and lifecycle management.
• Implement model serving solutions to deploy and manage realtime inference pipelines.
• Work closely with our product engineering and data science teams to build and maintain a data platform that scales with our growing customer base.
• Establish and enforce best practices for data and ML pipeline versioning experimentation and reproducibility.

What you bring along

• 3 years of experience in data engineering ML Engineering or a related field with a strong focus on MLOps.
• Experience in building and managing data pipelines that feed into machine learning models.
• Very good knowledge of Python; experience with PySpark is appreciated.
• Handson experience with data engineering tools and platforms; a background in Databricks is highly valued.
• Experience with MLFlow for model tracking and lifecycle management.
• Familiarity with model serving technologies and deploying models for realtime inference.
• Familiarity with CI/CD tools and processes including Jenkins Git or similar.
• Ability to wear multiple hats and thrive in a startup environment where flexibility and initiative are key.
• A mindset that embraces continuous improvement automation and scalability particularly in customer onboarding and deployment processes.

The tools you will be using

• Python
• PySpark
• Databricks
• MLFlow
• Model Serving Technologies
• CI/CD Tools (e.g. Jenkins Git)
• Cloud Platforms (AWS)
• Data Engineering Tools (Apache Spark DBT)

Cherry Ventures is an equal opportunity employer and values diversity. We do not discriminate on the basis of race religion colour national origin gender sexual orientation age marital status or disability status.