AI Jobs in Berlin

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As a Senior Software Engineer on the AI Voice Agent team, you will work on real-time systems involving live audio streaming and latency optimization integrated with speech providers. You will build and improve conversation intelligence systems that manage LLM layers, including prompt construction, context management, function calling, and dialogue management to create natural, actionable phone conversations. You will develop the action framework allowing configurable API calls with branching logic and runtime execution, supporting tasks like data lookup and ticket creation during calls. You'll manage knowledge ingestion, storage, and retrieval to enhance agent memory and learning over time. You will collaborate with designers to enable customers to create, configure, test, and deploy voice agents through intuitive product experiences. Additionally, you will help develop evaluation frameworks, analytics, call quality metrics, and monitoring instrumentation, and participate in on-call rotation duties.

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Design, automate, maintain, and optimize Python ETL pipelines (Spark/Ray) for large-scale multimodal data. Build and maintain data cataloging, lineage, quality tooling, integrity verification, access controls, and lifecycle management systems. Provide guidance, internal tools, and documentation to colleagues on data best practices. Serve as a custodian of the company’s datasets, ensuring overall data health, quality, and discoverability.

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As an AI Trainer - Junior Journalist, your responsibilities include crafting original, clear, and fact-checked responses based on project guidelines, generating prompts that challenge AI, defining comprehensive scoring criteria to evaluate the accuracy of AI's answers, and following style and quality standards to ensure consistency. You will help train AI models by shaping how they understand and generate human-like text, focusing on reasoning, logic accuracy, nuance, and clarity. The work is project-based and non-permanent, involving tasks estimated to require around 10–20 hours per week during active phases of the project.

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Contributors may design original computational STEM problems that simulate real scientific workflows, create problems requiring Python programming to solve, ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems requiring non-trivial reasoning chains and creative problem-solving approaches, verify solutions using Python with standard libraries such as Numpy, Pandas, Scipy, and scikit-learn, and document problem statements clearly while providing verified correct answers.

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Build and ship backend features for Taktile's AI agent platform in Python (FastAPI) deployed on AWS serverless infrastructure. Own work end-to-end by collaborating on scope, implementation, testing, releasing, and iterating based on real usage and customer feedback. Improve how agents run, connect to external tools, and behave when errors occur. Use AI tools daily to move faster, improve quality, and build AI-native capabilities. Review pull requests in depth, improve test coverage and CI/CD, and raise engineering excellence and reliability. Engage in team rituals including daily syncs, planning sessions, demos, and technical deep-dives. Grow professionally by learning from experienced team members, contributing to foundational product layers, and participating in cross-team learning groups. Participate in daytime operations duty and join an on-call rotation to support system ownership and DevSecOps skill growth.

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Contributors may design rigorous electrical engineering problems reflecting professional practice, evaluate AI solutions for correctness, assumptions, and constraints, validate calculations or simulations using Python (NumPy, Pandas, SciPy), improve AI reasoning to align with industry-standard logic, and apply structured scoring criteria to multi-step problems.

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Contributors may design rigorous energy engineering problems reflecting professional practice; evaluate AI solutions for correctness, assumptions, and constraints; validate calculations or simulations using Python (NumPy, Pandas, SciPy); improve AI reasoning to align with industry-standard logic; and apply structured scoring criteria to multi-step problems.

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Contributors may design rigorous electrical engineering problems reflecting professional practice; evaluate AI solutions for correctness, assumptions, and constraints; validate calculations or simulations using Python (NumPy, Pandas, SciPy); improve AI reasoning to align with industry-standard logic; and apply structured scoring criteria to multi-step problems.

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Design, build, and operate AI agents that power critical parts of Langdock's operations including customer support automation and internal workflows. Own production agents end-to-end by designing, deploying, monitoring, and improving the AI agents that handle real customer interactions and internal workflows. Investigate and fix issues when agents misbehave by digging into logs to identify root causes. Manage agent reliability, cost, and quality by tracking performance, costs, failures, and reasons; set budgets, tune behavior, adjust governance rules, and ensure agents perform effectively. Design the orchestration layer to define team structures, set approval gates, and build operational infrastructure for safe and scalable autonomous agent work. Integrate agents with internal and external APIs to provide context and capabilities. Constantly experiment with new models, techniques, and use cases by benchmarking and shipping improvements.

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Contributors may generate prompts that challenge AI; evaluate AI-generated solutions for correctness, assumptions, and logic; improve AI reasoning to align with first principles and accepted standards; and apply structured scoring criteria to assess multi-step problem solving.