Salary: 65.000 - 100.000 € per year Requirements: Several years of proven experience in MLOps, including end-to-end machine learning lifecycle management Strong programming skills in Python and C++ Familiarity with MLOps tools like MLFlow, Airflow, or Kubeflow. Experience designing and managing CI/CD pipelines for machine learning projects with experience in CI/CD tools (e.g., Jenkins) Proficiency in automation tools for streamlining ML operation Experience in Natural Language Processing (NLP) and Computer Vision (CV), workflows and metrics Hands-on experience in model validation, testing, and deployment to production Strong verbal and written communication skills in English Responsibilities: As a (Senior) MLOps Engineer, you will play a crucial role in building and maintaining the infrastructure and processes required to support machine learning operations. You will be responsible for preparing datasets, evaluating machine learning models using key performance indicators (KPIs), validating and deploying models, and ensuring their seamless integration into production systems (embedded and Cloud). Additionally, you will design and implement CI/CD pipelines for machine learning, automate ML operations, and utilize cloud-based solutions, such as AWS with Terraform, to enhance scalability and efficiency. This position requires a proactive individual with a strong foundation in MLOps practices, cloud platforms, and automation tools. Prepare and analyze datasets to support machine learning model development and training Assess natural language processing and computer vision models using relevant KPIs and metrics Validate models to ensure they meet performance standards and align with project requirements Deploy machine learning models into production environments with scalability and reliability Continuously monitor deployed models to ensure optimal performance and address issues as they arise Design, develop, and maintain CI/CD pipelines to streamline ML model development and deployment workflows Automate repetitive and manual processes involved in machine learning operations to improve efficiency Implement and manage MLOps solutions on AWS, leveraging Terraform for infrastructure as code Technologies: Airflow AWS CI/CD Cloud Computer Vision Embedded Support Jenkins Kubeflow Machine Learning Mobile Python Terraform C++ DevOps More: Cinemo is a global provider of highly innovative infotainment products that make every screen an opportunity. Its range of award-winning, fully integrated, low-footprint digital media offerings combine high performance with high quality and are truly system agnostic. Whether embedded, as mobile apps or through the cloud, Cinemo supports all digital media scenarios for any industry and any device. Its product portfolio is designed and built to deliver excellence, accelerate time to market, and lower TCO for its clients while creating digital media experiences that matter. Founded in 2008, and with a strong history of industry firsts, Cinemo is the partner of choice for more than 40 market-leading OEMs and over 20 tier-1s. The company works with the top high-tech and consumer electronic companies as well as global music and video content providers. Cinemo’s global team of 300 innovative thinkers from 40 nationalities continuously delivers groundbreaking innovation.