Top Machine Learning Jobs in Berlin

The Applied Research Scientist will develop advanced tools for enhancing written English using NLP, ML, and DL technologies, contributing to product development and research strategy.

The role involves data extraction from medical records, ensuring data quality, and collaborating with cross-functional teams to support product development and clinical documentation.

The Account Executive will drive new business by selling SaaS solutions to Managed Service Providers in the Nordics, managing the full sales cycle, and achieving revenue targets.

Lead the AI Foundations team, focusing on machine learning applications in AdTech, ensuring compliance, mentoring, and driving AI adoption and excellence.

As a Principal Software Engineer, you'll lead multiple teams in Risk Management, designing cloud-based solutions, mentoring engineers, and driving innovation.

As an ML Research Engineer, you will develop computational methods and infrastructure to enhance molecular simulations and machine learning force fields for materials discovery.

Kittl seeks innovative individuals for engineering and product roles. Applicants should show passion for design, ownership, and collaboration. Areas include frontend, backend, full stack, data, and product management.

As a Scientific Software Engineer specializing in polymer simulations, you'll design workflows for atomistic simulations, integrate AI with simulations, and collaborate on experimental validations, bridging theory with real-world applications.

As a Staff Machine Learning Engineer, you will design and build ML systems to enhance advertising experiences, collaborate with teams, mentor others, and innovate in areas like generative AI and NLP.

The Senior Machine Learning Engineer will develop and deploy ML-based software, collaborate with stakeholders, and enhance Smartly's MLOps platform, impacting advertising experiences.

The Director of Business Development at Moloco will drive revenue growth, close partnerships, and support expansion across EMEA while focusing on AI-powered advertising solutions.

Lead the Pricing and Data domains within Logistics, managing a team of engineers and data scientists to optimize delivery pricing and operations across markets.

The Senior Machine Learning Engineer will design MLOps systems, manage model lifecycles, mentor teams, and contribute to technology strategies to improve machine learning solutions.

As a C++ Engineer, you will develop machine learning features, integrate models, maintain SDKs, and collaborate across teams for software performance and enhancements.

The Vice President, Product will define and scale the product vision for an AI-driven trade platform, overseeing product strategy and leading teams across multiple functions to enhance automation and address customer needs effectively.

As a Senior Machine Learning Scientist, you'll identify ML opportunities, work with teams to research algorithms, conduct data analysis, and prototype solutions for customer value, while applying advanced ML techniques and collaborating with engineers for production deployment.

As a product engineer at Intercom, you will develop technical plans, write Ruby code, collaborate with cross-disciplinary teams, and mentor other engineers while solving customer problems.

The Applied Science Manager leads a team of scientists and engineers to develop solutions for Ads Personalization, focusing on real-time recommendations. Responsibilities include guiding research, ensuring high-quality project execution, and promoting collaboration across teams.

The AI Business Development Specialist will identify business opportunities, build client relationships, and promote AI solutions in various sectors, with a focus on the MENA region.

The role involves building AI solutions for logistics, focusing on designing production-grade systems, problem-solving, and technical ownership without people management responsibilities.

Lead the development of large language models for marketing technologies, optimize AI solutions, and mentor junior team members to drive innovation and quality.

The role involves enhancing search systems through advanced NLP and IR methods, developing scientific roadmaps, mentoring junior scientists, and applying machine learning solutions for better customer experiences.

As an Enterprise AI Adoption Manager, you will guide companies in adopting AI, manage enterprise accounts, drive AI transformation, and work closely with engineering and product teams to deliver value.

Develop core methods for temporal ontology extraction and contradiction detection. Collaborate with research teams and publish findings. Prototype ideas, create datasets, and validate methods.

Lead the new Revenue Technology domain, managing teams, driving technical excellence, optimizing processes with AI, and representing engineering in commercial discussions.