Top Artificial Intelligence Jobs in Berlin

Build production evaluation and observability infrastructure for multimodal LLM agents used in audit workflows. Responsibilities include creating online and offline evaluations, golden datasets, quality gates, human review workflows, trace analysis, data retention and replay systems, monitoring, and experiment management. The role also involves improving agent speed, reliability, quality, and cost through backend engineering, data architecture, retrieval optimization, and collaboration with engineering teams.

The role involves sourcing and evaluating AI infrastructure founders, supporting them through early stages of investment, and representing the firm with technical expertise.

Work directly with founders and leadership to execute company strategy, own strategic and operational projects from 0 to 1, and drive priorities across Product, Sales, Finance, Operations, and Venture Development. The role requires proactive execution, structured thinking, comfort with ambiguity, and strong interest in technology, operations, and business strategy within a fast-growing startup.

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.

Lead technical strategy and architecture for AI-powered content systems across the organisation. Define standards for AI evaluation, governance, observability, security, and reliability. Influence roadmaps with senior stakeholders, identify risks and opportunities, mentor senior engineers, and lead complex cross-team initiatives. Combine hands-on delivery of AI/ML production systems with organisation-wide technical direction to ensure scalable, measurable impact on product and learner outcomes.

Build and operate an AI-first marketing automation layer: design agentic operating models, embed with marketing teams to find and automate bottlenecks, develop multi-agent harnesses, integrate APIs and data pipelines, deploy and maintain solutions, and scale reusable tools and playbooks while upskilling marketers.

Record short video and audio clips in German using clear, expressive, emotionally varied delivery, and transcribe spoken content from media clips. Work is fully remote with a flexible schedule and requires a quiet recording environment, 1080P camera, and comfort speaking on camera. Acting, theater, improv, vocal training, podcasting, customer support, or public speaking experience is beneficial but not required.

Own a revenue-generating product end-to-end, build AI-driven tools and automations, run data analysis to inform decisions, and work across product, growth and operations. Move quickly from idea to production, make strategic calls, and collaborate closely with founders in a fast-paced, remote-first startup.

Lead SEO, Generative Engine Optimisation (GEO), and HubSpot website management to drive organic pipeline. Own technical, on-page, off-page SEO, AI search presence, CRO experiments, multilingual site governance, agency coordination, and reporting that ties organic activity to revenue.

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.

Lead and deliver high-priority AI-driven projects end-to-end, translate AI opportunities into practical implementations, coordinate cross-functional teams, optimise operations through automation and data-driven workflows, and drive measurable business impact across user acquisition and product functions.

The Customer Success Manager (SEO) will onboard clients, advise on SEO strategies, review performance, and collaborate with teams to enhance customer enablement.

The GTM AI Engineer will automate workflows, manage HubSpot systems, implement lead scoring models, and enhance data processes to boost revenue and efficiency.

As a Sales Development Representative, you will cultivate relationships with B2B clients, generate interest in renewable energy solutions, and drive customer acquisition and company growth.

As a Continuous Improvement Manager, you'll analyze operations, drive implementation of AI-powered improvements, and build strong relationships with customers while ensuring measurable outcomes and efficiencies.

Own and evolve cloud infrastructure on AWS using Terraform; manage and scale Kubernetes clusters; build and improve CI/CD pipelines; implement monitoring, logging and alerting; configure CDN infrastructure; and support ML workloads in production to improve developer experience and observability.

Build and maintain scalable React + TypeScript frontend applications and AI agent interfaces, integrate with backend APIs and AI systems, implement component-based architecture, ensure performance, accessibility, testing, and collaborate within a small cross-functional product squad.

Architect and build an AI-native automation and orchestration toolchain (fusing traditional tools with foundation models), enable and mentor early adopter teams, standardize practices across departments, drive infrastructure-as-code and CI/CD adoption, contribute to the IT/Sec operating system, and champion cross-departmental adoption of automation and AI platforms.

Lead strategy and roadmap for an internal AI-as-a-Platform, coordinate cross-functional teams to implement AI use cases, ensure compliance and governance, support GTM for AI features, manage agile product development, and use data and model outputs to evolve the platform.

Design, build, and maintain production-grade AI/LLM backend services and APIs. Develop cloud-native architectures on AWS, extend Terraform infrastructure, implement CI/CD, testing, and monitoring. Work with agentic orchestration frameworks (e.g., LangGraph) and integrate LLM APIs (OpenAI, Anthropic, Google) into scalable products, collaborating with cross-functional teams.

Build and maintain an internal AI provisioning platform for LLM access, observability, governance, security, cost management, and production monitoring while partnering with AI engineers on cloud-native, agentic workflows.

As an AI Research Engineer focused on AI Safety, you will develop techniques for evaluating AI products, enhance decision-making via uncertainty quantification, and ensure robustness against adversarial attacks.

Senior AI/ML Consultant focuses on transforming AI ambitions into production-ready systems, guiding clients through the AI integration process and building operational AI strategies. The role includes leading projects, mentoring junior staff, and contributing to thought leadership in Data & AI.

As Engineering Manager, lead the Edge AI team, formulate sprint roadmaps, oversee AI system migration, ensure performance, and foster an engineering culture. Hire and mentor team members while managing stakeholder engagement.

Own customer workstreams that transform MedTech regulatory, quality, R&D, and compliance workflows into practical AI-powered solutions. Responsibilities include discovery, workflow design, implementation support, testing, delivery, workshop development, gap analysis, impact assessment, output review, and translating customer feedback for Product and Engineering. The role requires deep medical device regulatory expertise, strong project ownership, customer communication, hands-on execution, and active use of AI tools.