Top Artificial Intelligence Jobs in Berlin

Build and qualify enterprise sales pipeline for the DACH market through consultative, signal-driven outbound engagement. Research named accounts, conduct senior-level discovery conversations, qualify opportunities in HubSpot, and hand off BANT-qualified pipeline to Account Executives. Use AI tools and lightweight agents to improve research, outreach, enrichment, and signal monitoring. Native German and English proficiency are required, with potential promotion to Account Executive after six months.

Enterprise Account Executive responsible for acquiring new enterprise customers, exceeding ARR quotas, leading sophisticated outbound campaigns, navigating multi-stakeholder buying committees, and closing complex SaaS deals. The role engages HR, Communications, IT, and executive stakeholders, develops strategic business cases, and collaborates with SDRs, Partnerships, Marketing, Solution Engineering, Customer Success, and Product teams. Candidates need enterprise SaaS sales experience, strategic selling expertise, fluent German and English, and a strong hunter mentality.

Partners with Sales, Product, Engineering, and Improvement teams to win and expand manufacturing customers. Leads discovery, maps factory workflows, identifies bottlenecks, translates operational challenges into AI use cases, supports pilots and deployments, quantifies ROI, and develops repeatable value-selling playbooks. The role requires expertise in continuous improvement, Lean, operational excellence, or industrial engineering, along with manufacturing operations experience and the ability to communicate effectively with shop-floor and executive stakeholders.

Lead R&D for industrial robotic manipulators, including modeling, planning, control, perception, machine learning, simulation, and hardware integration. Develop and test robotic prototypes, planning algorithms, middleware, software architectures, pose estimation, segmentation, and autonomous grasping systems. Deploy and validate solutions using ROS-compatible hardware, sensors, robot arms, and real-world environments.

Build Almetra’s marketing function from the ground up, owning positioning, messaging, go-to-market strategy, demand generation, ABM, content, events, partnerships, metrics, and reporting. The role partners closely with founders and sales leadership, establishes repeatable revenue-generating marketing motions, and gradually builds and leads the marketing team as the company scales.

Drive continuous improvement initiatives for manufacturing customers using AI-powered computer vision insights. Analyze production data and assembly processes, identify inefficiencies, recommend measurable improvements, train customer teams, guide implementation, track outcomes, and collaborate with engineering, data science, product, and sales teams. Apply Lean and CI best practices while helping develop scalable AI-enabled improvement methods.

Partner with government customers and partners to design, prototype, and deploy AI solutions (computer vision, LLMs, generative/agentic AI). Create technical collateral, lead hands-on trials and deployments using NVIDIA hardware/software, and advocate product requirements across product, sales, and engineering teams.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Fine-tune and post-train open-weight LLMs using methods such as SFT, LoRA, QLoRA, DPO, and GRPO. Build training data and evaluations, diagnose model failures, improve personalization and multilingual behavior, accelerate reproducible training workflows, and deploy models to production. The role involves using real user behavior to guide iterations across a large-scale AI companionship platform, with collaboration across AI, product, web, DevOps, and leadership teams.

Manage full-cycle technical recruiting for AI, machine learning, and AI safety teams. Responsibilities include sourcing niche and passive talent, market mapping, talent-pool development, candidate engagement, stakeholder collaboration, offer negotiation, candidate experience, and recruitment-process improvement. The role requires strong knowledge of AI research recruiting, bilingual German and English communication, and the ability to operate effectively in a fast-paced startup environment.

Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship end-to-end product features, set technical direction, evaluate LLM reliability and trade-offs, and accelerate validated learning through close collaboration with engineering, product, and design teams.

Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship production software, establish technical direction, and partner with product and design teams to accelerate validated learning. The role requires strong backend and distributed-systems expertise, hands-on LLM product experience, and practical use of AI coding tools.

Serve as a technical advisor for digital-native and startup customers, leading discovery, cloud and AI architecture, demonstrations, workshops, proofs of concept, and production-readiness engagements. Translate business goals into Azure solution plans, remove technical blockers, influence technical decision-makers, and accelerate Azure adoption and consumption. Partner with account teams, specialists, customer success, engineering, and product teams to advance opportunities, create reusable technical patterns, and support complex customer sales motions.

Builds and deploys AI-enabled workflows across Neko, helping teams identify business problems, redesign processes, adopt solutions, and measure impact. The role combines consulting, hands-on AI development, process mapping, training, workflow adoption, and iteration. Success is measured by sustained usage, efficiency gains, and the ability to help teams become more capable of building with AI.

Build and operate Raisin’s internal AI platform, including governed model access, agent integrations, security controls, audit logging, infrastructure, observability, and incident response. Develop agentic software-development workflows and reusable AI tooling. Partner with internal teams, security, legal, and compliance to define platform capabilities, improve adoption, and balance model cost, latency, quality, and reliability.

Design and build production conversational AI agents for fashion discovery, recommendations, and shopping. Develop RAG pipelines, prompts, LLM integrations, evaluation frameworks, and agent workflows. Optimize assistant performance against engagement, conversion, and retention metrics while collaborating with product, engineering, and data science teams. The role includes architecture ownership, experimentation, deployment, and mentoring colleagues in applied AI and agent development.

Join Welo Data’s Swahili contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertising, or chatbot evaluation; prompt creation; and cultural and linguistic accuracy review. Applicants must be native or near-native Swahili speakers based in Kenya, Tanzania, or the Democratic Republic of Congo, with English proficiency, digital-tool comfort, and strong attention to detail. Projects vary in duration and compensation, with details provided before participation.

Lead development of LLM-powered legal AI features: implement chat interfaces and backend integrations, build and optimize RAG and retrieval pipelines, design agent orchestration, create evaluation/benchmarking and monitoring infrastructure, and enforce security and privacy while collaborating with Product and Legal Engineering.

Develop AI-driven products through hands-on software development and product engineering. Build minimum viable products, solve problems creatively, and help shape future AI applications. The role is available remotely or in Boston and Chicago, with contract options ranging from two weeks to three months or full-time, plus potential revenue sharing.

Build scalable data warehouses, cloud infrastructure, AI workflows, and data-driven applications. Integrate data from multiple systems, ensure accessible and consistent data, evaluate AI use cases, and collaborate with analytics, product, and software engineering teams in an agile environment.

Own the DACH and Nordics enterprise sales territory, managing the full B2B SaaS sales cycle from pipeline generation through closing and account expansion. Build a $1M+ new-business ARR territory, maintain 4.5x pipeline coverage, exceed quota, develop executive relationships, and open enterprise segments across airlines, gaming, travel, and telecommunications. Collaborate with SDRs, marketing, partnerships, product, and customer solutions teams while delivering accurate forecasts. The role requires approximately 30% regional client travel and occasional London team visits.

Develop and maintain full-stack product features for an AI-powered legal technology platform. Build backend APIs and frontend interfaces, collaborate with product and design teams, ensure scalable and secure architecture, contribute to technical decisions, and integrate AI tools and agents. The role requires strong Python, FastAPI, asynchronous programming, and TypeScript experience, with Svelte and LLM product experience as advantages. This is a hybrid position based in Berlin.

Build production-grade evaluation, observability, and data infrastructure for multimodal LLM agents. Develop online and offline evaluation pipelines, golden datasets, quality gates, replay and retention systems, and trace analysis workflows. Use analytical databases to identify quality, latency, reliability, and cost issues. Operate observability and experimentation tooling while partnering with backend engineers to improve retrieval and reasoning agents.

Build and operate the company’s AI platform, including model gateways, routing, cost optimization, usage and billing systems, agent infrastructure, tenant isolation, secrets management, European cloud infrastructure, GPU model serving, observability, testing, and safe production releases. The role requires close collaboration with the founding team, ownership from design through operation, and practical involvement with LLMs, embeddings, evaluations, fine-tuning, and agentic engineering workflows.

Manage complex enterprise accounts throughout the sales cycle, from pipeline generation through AI product deployment. Develop account strategies, lead customer programs, own consumption revenue targets and forecasts, analyze account metrics, and advise executives on AI adoption. Collaborate with solutions, engineering, research, marketing, finance, product, and operations teams while contributing to customer events, company strategy, recruitment, and organizational growth.