Match score not available

MLOps Engineer

Remote: 
Full Remote
Contract: 
Work from: 

Offer summary

Qualifications:

Proficient in DevOps practices, Experience with CI/CD pipelines, Expertise in Kubernetes and Docker, Hands-on experience with AWS.

Key responsabilities:

  • Design and maintain scalable pipelines
  • Develop methods to evaluate model performance
COMPREDICT logo
COMPREDICT https://compredict.ai/
11 - 50 Employees
See more COMPREDICT offers

Job description

Your mission
As an MLOps Engineer, you will play a critical role in ensuring our machine learning models transition seamlessly from research to production. These models analyze car data over time to generate actionable insights, such as:
  • Predicting tire pressure without traditional sensors.
  • Assessing a car's battery health to proactively identify potential issues.
Your primary responsibility is to design, implement, and maintain a robust, efficient, and secure pipeline that supports the entire lifecycle of machine learning models, from development to deployment and monitoring. As the number of deployed models grows, your expertise will be pivotal in managing model comparisons and maintaining performance standards.

Your Role in More Detail:

MLOps Pipeline Development and Optimization:
  • Design and maintain scalable pipelines for deploying machine learning models.
  • Ensure models are securely integrated into production environments with minimal latency.
  • Implement monitoring systems to track model performance and flag issues.
Model Comparison and Validation:
  • Develop methods to evaluate and compare the performance of different models.
  • Automate processes for validating model accuracy and consistency in production.
Collaboration:
  • Work closely with data scientists, developers, and stakeholders to understand their needs and provide tailored solutions.
  • Effectively communicate technical processes and outcomes to both technical and non-technical audiences.
Documentation and Knowledge Sharing:
  • Create comprehensive documentation for processes, pipelines, and workflows.
  • Provide training and guidance to team members on MLOps best practices.
Your profile

  • Proficient in modern DevOps practices and microservice architectures.
  • Experience with CT/CD pipelines and automation tools.
  • Expertise in Kubernetes and containerization technologies (e.g., Docker).
  • Familiarity with platforms such as KubeFlow, MLflow, or equivalent.
  • Hands-on experience with AWS or other cloud service providers.
  • Understanding of time series modeling and its data requirements.
  • Knowledge of deep learning concepts is a plus.
  • Strong ability to collaborate with cross-functional teams, including data scientists, engineers, and clients.
  • Clear and concise in verbal and written communication, with excellent documentation skills.
  • Fluent in both written and spoken English. German is a plus.
About us

COMPREDICT is driving the paradigm shift towards software-defined vehicles, offering next-level solutions for sustainable mobility. Founded in 2016 in Darmstadt, Germany, by Dr. Rafael Fietzek and Dr. Stéphane Foulard, our focus lies in developing Virtual Sensors for Mobility to optimize vehicle design, usage, and maintenance. We partner with and serve automotive manufacturers and Tier1 companies worldwide. With a diverse team of 35+ members from 10 different nations, we are on an exciting journey of growth and innovation.

Required profile

Experience

Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Collaboration
  • Communication

Field Engineer (Solutions) Related jobs