5 data analytics jobs found in Berlin

BERLIN, MUNICH Tasks Together with experienced colleagues, you will develop the architecture and implementation of modern AI and data-driven platforms in the cloud – with the goal of providing scalable solutions for machine learning and GenAI applications. Automate infrastructure deployment with tools like Terraform or Ansible and create the foundation for the reliable operation of AI workloads, training pipelines, and inference-related systems . Dive into the development and optimization of CI/CD and MLOps pipelines to efficiently train, version, and deploy production-ready models. Support in monitoring the performance of AI systems and distributed data platforms , detecting anomalies early using intelligent monitoring approaches, and initiating automated countermeasures. Actively contribute to the team, exchange ideas and shape the further development of our platforms – especially through prototyping AI applications, experimenting with...

Why voice? Because we're more than just a job! At voice,   we believe the greatest gift to frontline workers is time - time to care, connect, and be present.   Today, that time is lost to   busywork and complex systems   that pull them away from what matters most:   people   . Our vision is to change that by building AI companions   that seamlessly take over digital workflows. We don't replace humans with technology -   we amplify their impact. Our mission is backed with a   $50M Series A funding led by Balderton Capital, with support from HV Capital, Y Combinator and other leading VCs. Today, 2,000+ facilities trust voice, and over 200,000 users rely on our AI companion   to ease their daily workload. As a dynamic team, we combine first-in-class technology with meaningful social impact.   And now, we're looking for you to join us on this mission! Your Mission: Turning Machine Learning capabilities into real user value voice is more than a scribe...

Location Berlin Employment Type Full time Location Type On-site Department IT Your role We are looking for an experienced   (Senior) AI/ML Engineer   to join our   Central Data Platform   team and take ownership of the machine learning and GenAI infrastructure that powers advanced analytics and AI use cases across the organization. In this role, you will design, build, and maintain end to end ML pipelines in Vertex AI, ensuring that models move seamlessly from prototype to production ready, monitored, cost efficient, and compliant pipelines. You will also pioneer GenAI enablement, including retrieval augmented generation, embeddings, and AI driven applications, while embedding governance, reproducibility, and scalability from day one. This is a pivotal position with high impact on how AI and machine learning capabilities are delivered, scaled, and governed at Sunday Natural. You will act as the bridge between Data...

BERLIN, MUNICH Tasks As a Consultant Data Engineer (m/f/d), you will actively shape the data-driven future of our clients. You will develop modern data solutions and innovative data products, as well as AI-ready data platforms that help companies make informed and sustainable decisions. Your responsibilities will include, but are not limited to, the following: Support in the design and implementation of robust and scalable data products, data architectures and AI-ready data platforms. You will develop and optimize data pipelines for the integration and transformation of diverse data sources – using modern technologies such as SQL, Python, dbt, Snowflake, Databricks and leading cloud platforms (AWS, Azure, Google Cloud). You will work closely with our customers, analyze professional and technical requirements and translate these into tailor-made data engineering solutions with real added value. Providing and structuring high-quality data for...

Big tasks Development, implementation and optimization of machine learning models at the proof-of-concept level Scaling of machine learning models for use in production systems, taking into account performance, scalability and security. Design, testing and management of data pipelines for training and production systems Data acquisition, quality assurance, and feature engineering Close and independent collaboration with data scientists, software developers and other teams to integrate models into existing workflows Research, evaluation and selection of suitable machine learning algorithms and technologies, based on current research findings Target-group-oriented documentation and presentation of the developed models and their results Ideal conditions Studies in Computer Science, Computer Engineering, Mathematics, Statistics, Engineering or a comparable field of study Relevant experience in the development and implementation of machine learning...