Top Artificial Intelligence Jobs in Berlin

Develop and maintain full stack applications, integrate AI capabilities using APIs, and collaborate with stakeholders to enhance workflows.

Perform remote, part-time data tasks to improve German AI content, including data collection, evaluation, annotation, pairwise comparisons, counting tasks, and object tagging across audio, video, and images.

As an ML Engineer Intern, you will build and deploy ML models, design scalable infrastructure, and collaborate with data science teams in a fast-paced environment.

As an ML Engineer, you'll build and deploy scalable ML systems, optimize models, and collaborate with teams to improve content across platforms.

Support and improve ML/LLMOps and AI-agent infrastructure: evaluate LLM frameworks and APIs, build RAG pipelines, design agent evaluation systems, automate ML/data pipelines, and document findings.

As a Staff Product Engineer in AI, you will build and launch AI products, collaborate with ML scientists, and contribute across all software development phases while mentoring other engineers.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

The role involves engineering, testing, and the development of advanced frontend components for an AI-driven cybersecurity product, integrating AI features and ensuring best practices are followed.

The Fullstack Engineer will focus on product software engineering, agents framework engineering, and R&D in AI and cybersecurity. Responsibilities include hands-on engineering, testing, and integrating AI Agents into existing systems.

As an Account Executive, you will drive revenue growth by managing the sales cycle, engaging decision-makers, and negotiating multi-year SaaS agreements.

As an AI Research Engineer, you will develop signal processing solutions, collaborate across teams, and apply AI in real-world scenarios within defence.

The AI Content Evaluator will review and assess content for alignment with guidelines, ensuring quality and consistency in annotation. Responsibilities include evaluating various content types, applying structured criteria, and adhering to project guidelines.

Lead company-wide AI and automation adoption: run internal programs (hackathons, enablement, dogfooding), conduct AI market watch, produce guidance and content, evangelize successes, and manage and scale the Automation team while overseeing cross-functional delivery and OKRs.

As the AI Agents Solutions Architect at Kraken, you'll design and build an AI-native finance operating system, automating finance operations and ensuring compliance in a regulated environment.

The Principal AI Scientist will develop customized LLM solutions, enhance existing models, and incorporate new AI techniques. Required to collaborate with teams and optimize performance for generative AI applications.

Develop and maintain AI and ML algorithms, create data pipelines, collaborate with cross-functional teams, and implement solutions for business requirements.

The Ecosystem Growth Manager will drive the onboarding of GPU providers, AI builders, and strategic enterprise partnerships to enhance the AIVM ecosystem, addressing Web3 challenges and establishing a decentralized infrastructure.

As a Senior Forward Deployed Engineer, you'll deliver AI solutions, engage with customers, and lead project lifecycles, including deployment and integration.

Design and deploy AI-powered HR solutions, integrating and automating HR workflows. Ensure compliance, governance, and drive adoption of tools among HR team members.

The AI Applied Scientist Intern will tackle complex problems using deep learning, statistical analysis, and large datasets, collaborating with a team to implement AI solutions that generate economic impact.

The role involves architecting AI solutions for compliance, ensuring regulatory adherence, automating processes, and enhancing team capabilities through technology and training.

Design, build, and optimize high-performance AI infrastructure systems to support intelligent agents, ensuring reliability and scalability for millions of users.

The AI Engineering Intern will design, test, and deploy scalable AI systems, integrate models, and work on inference optimization, collaborating with data scientists on complex problems.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

AI Engineers at QuantCo design, build, and implement applied AI systems, working with data scientists to optimize inference, develop scalable solutions, and integrate AI into enterprise operations.