Top Artificial Intelligence Jobs in Berlin

Build AI-powered features, LLM integrations, and multi-step agent workflows for requirements and systems engineering software. Integrate agents with internal data sources, reason over requirements documents and system specifications, address security and data privacy, and deploy AI capabilities into production. The role requires software engineering experience, hands-on LLM integration, end-to-end ownership, and collaboration in a startup environment.

Own end-to-end infrastructure delivery for strategic physical AI customers, from discovery and architecture through production rollout. Build cloud compute orchestration, platform services, onboarding environments, observability, security, and cost controls for simulation, training, inference, and batch workloads. Debug across infrastructure layers, productize recurring customer needs, and shape the physical AI platform roadmap. Partner with customers, Field CTO, Product, and Engineering while using AI coding tools to accelerate production engineering.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

Supports Account Managers and client teams by coordinating delegated tasks, tracking deadlines and follow-ups, preparing updates, managing workflows, communicating in German and English, reviewing AI-generated work, and improving repeatable account processes. The role requires strong client judgment, attention to detail, prioritization, technical adaptability, and hands-on use of AI tools and agents in a remote, async environment.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Lead the company’s Physical AI research and engineering function as a hands-on technical leader. Define research priorities, design and train Transformer-based models, establish rigorous offline and real-world evaluations, integrate systems with physical robots, and analyze failures across data, models, hardware, and environments. Build a focused team, guide technical architecture and experiments, translate customer needs into requirements, and deliver measurable improvements through deployed models, benchmarks, evaluation systems, or data products.

Build and productionize AI-powered customer support systems, partnering with ML scientists, product, and design teams. Develop prototypes, scalable ML products, and software across Python ML systems and Rails applications. Contribute throughout the development lifecycle, measure customer impact, improve reliability and technical standards, and mentor and hire engineers.

Assess and evaluate AI-generated technical content, craft and answer advanced ML/AI questions, identify errors and hallucinations, rank responses by correctness and clarity, and provide precise feedback to improve model performance.

Build and operate AI agents for Operations and Customer Success workflows, redesigning processes for autonomy and quality. Own agent context, CRM and data integrations, evaluation, prompt optimization, quality assurance, and impact measurement. Translate business needs into technical solutions, collaborate with Leadership, IT, and Product, and enable teams to use AI effectively. The role requires production-oriented technical skills, data fluency, strong communication, and experience with automation tools, Salesforce, and agent platforms.

Evaluate AI chatbots and language models in German via structured written and voice interactions. Submit ratings, write-ups, screenshots or recordings per task specs. Work is task-based, remote, flexible, paid hourly, and requires passing language and technical assessments and identity verification.

Design, build, and deploy AI-powered products using frontier LLMs. Create agents, RAG systems, and backend services; evaluate and improve model quality, ensure trust/privacy, and collaborate with product, design, and finance teams.

Own the technical design and production delivery of multi-component AI systems. Build evaluation frameworks for nondeterministic behavior, data pipelines, feedback loops, model-tool boundaries, and agent harnesses. Optimize latency and cost through streaming, caching, routing, and prompt design. Develop internal tooling, assess external models and datasets, support APIs and SDKs, mentor engineers, and participate in 24/7 on-call operations.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

The AI Architect will design scalable AI architectures, develop monitoring mechanisms, ensure compliance, create RAG pipelines, and collaborate with stakeholders.

Build and operate Typeform’s internal AI Operations capability for R&D. Identify and prioritize AI opportunities, discover workflows, design and deliver AI-native solutions, and manage their lifecycle after launch. Responsibilities include improving enterprise AI tools, coordinating access and governance, evaluating reliability and security, supporting automations and agents, measuring adoption and value, and partnering with Product, Engineering, IT, InfoSec, Finance, and other teams.

Develop and implement GEO strategies that improve client visibility across AI search environments, LLMs, AI assistants, and generative platforms. Analyze AI visibility, citations, sentiment, Share of Voice, and rankings; turn insights into recommendations, media plans, budgets, reports, and client presentations. Onboard clients, support pitches, manage relationships, collaborate cross-functionally, and develop GEO playbooks, training, and best practices.

Citrine Informatics invites applicants to submit resumes for general opportunities. They review applications periodically for potential new roles in AI-driven materials and chemicals.

Join Welo Data’s Canadian French contributor network for potential remote AI projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and details provided before each assignment.

Join Welo Data’s French AI Trainers Network as a flexible contributor supporting annotation, evaluation, and prompt creation projects. Contributors may label text, images, or audio; assess search results, advertisements, and chatbot responses; create prompts for large language models; and ensure cultural and linguistic accuracy. This is a talent community rather than an active opening, with project details and compensation provided when assignments become available.

Advise C-level life sciences and healthcare executives on AI and data strategies, lead large-scale digital transformations, develop client relationships, generate consulting business, oversee major client portfolios, and guide cross-functional teams in designing, implementing, and scaling AI and data solutions.

PhD-level research intern to investigate and prototype 3D computer vision methods (SLAM, VIO, localisation, reconstruction). Survey SOTA, design and benchmark algorithms under real-world conditions, convert ideas into prototypes, and report results to a distributed European team focused on deployable defence-grade spatial perception.