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ML Ops Engineer - Berlin

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Cherry Ventures

1mo ago

  • Job
    Full-time
    Mid Level
  • Data
    IT & Cybersecurity
  • Berlin
    Remote

AI generated summary

  • You should have 3+ years in data or ML engineering, strong Python skills, data pipeline experience, familiarity with MLFlow, CI/CD tools, and a flexible mindset for a startup environment.
  • You will design and manage data pipelines, implement CI/CD workflows, automate customer onboarding, collaborate with teams for model deployment, and maintain tools for model tracking and monitoring.

Requirements

  • 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.
  • Hands-on 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 real-time 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.

Responsibilities

  • 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 real-time 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 real-time 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.

FAQs

What is the job title for this position?

The job title is ML Ops Engineer with a focus on Data Engineering.

Where is the location of the job?

The job is based in Berlin, Germany.

What type of employment is being offered?

This is a full-time position.

Who is supporting the hiring for this position?

Cherry Ventures is supporting the hiring for this position.

What industry is Plato focused on?

Plato is focused on the global wholesale industry, specifically the $48 trillion market.

What are the key responsibilities of this role?

Key responsibilities include designing and managing data pipelines, implementing CI/CD for data workflows, automating customer onboarding, and collaborating with data scientists on model deployment.

What skills are required for this position?

Required skills include experience in data engineering and MLOps, proficiency in Python (with PySpark being appreciated), familiarity with MLFlow, and knowledge of CI/CD tools and processes.

How many years of experience are needed for this role?

A minimum of 3 years of experience in data engineering, ML engineering, or a related field is required, with a strong focus on MLOps.

What technologies will be used in this role?

Technologies include Python, PySpark, Databricks, MLFlow, CI/CD tools, and cloud platforms like AWS.

What is the company culture like at Plato?

Plato fosters a dynamic startup environment where flexibility, collaboration, and the ability to wear multiple hats are highly valued.

Are there opportunities for professional growth in this position?

Yes, there are opportunities for continuous improvement and scalability within the role, particularly in customer onboarding and deployment processes.

Is there a focus on diversity and inclusion at Cherry Ventures?

Yes, Cherry Ventures is an equal opportunity employer and values diversity, ensuring no discrimination based on race, religion, gender, or other status.

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Cherry Ventures

Founders first and investors second.

Venture Capital & Private Equity
Industry
11-50
Employees
2012
Founded Year

Mission & Purpose

Cherry Ventures is an early-stage venture capital firm led by a team of entrepreneurs with experience building fast-scaling companies such as Zalando and Spotify. The firm backs Europe's boldest founders, usually as their first institutional investor, and supports them in everything from their go-to-market strategy and the scaling of their businesses. Cherry Ventures has previously invested in the seed stage of over 90 companies across Europe, including FlixBus, Auto1 Group, Flaschenpost, Infarm, Forto, SellerX, Juni, and Flink. Cherry Ventures is based in Berlin and invests across Europe with operations in London and Stockholm.