Machine Learning Engineer

• Build LLM applications.
• Develop dialogue-based systems and semantic search and integrate them into the domain-specific applications of the industry solution.
• Set up and maintain RAG systems, including knowledge-base management: indexing, updates, and clean source-separated storage of structured and unstructured content.
• Operation and monitoring.
• MLOps in production: observability, structured logging, and error analysis.
• Ensure systems run reliably, not just that they worked once.
• Deploy agents to production, from development and integration through to stable delivery.
• Improve systems based on monitoring data, testing, and user feedback.
• Identify new AI use cases, prototype them, and build data pipelines from preprocessing and model development to production.

AI Engineer

• Design, build, and run agentic workflows
• Own quality end to end
• Design human-in-the-loop workflows
• Embed with delivery teams
• Drive adoption of AI within RobCo

Senior Applied AI Engineer

• Own the development, curation, and distribution of a centralized catalog of reusable AI components
• Define and promote standards and governance for reusable assets
• Collaborate with AI Solution Engineers to identify components built during co-build engagements
• Manage the lifecycle of the component catalog: intake, review, tagging, publishing, deprecation, and quality assurance
• Act as a technical authority on AI development patterns
• Work with the enterprise AI Foundation area to ensure adherence to infrastructure, security, and compliance standards
• Monitor usage and impact of catalog components
• Contribute to the broader AI Enablement community by sharing knowledge

Lead AI Assets Manager

• Evolve the Interactive Learning Plugin's recommendation system.
• Build and operate applied models.
• Define what recommendation quality means.
• Ship incremental improvements.
• Partner across disciplines.

Senior Machine Learning Engineer, Developer Advocacy

• Design, build and evolve scalable ML and generative AI systems that deliver measurable value in customer-facing and operational use cases.
• Develop robust end-to-end pipelines for training, evaluation, deployment, monitoring, and continuous improvement of AI solutions in production.
• Collaborate closely with product, engineering, data, and business stakeholders to bring AI capabilities into core digital healthcare systems and operations
• Explore and implement cutting-edge AI advancements to continuously enhance innovation and solution effectiveness
• Take ownership as AI Technical Owner, shaping the technical roadmap and driving the full AI lifecycle across strategic initiatives
• Contribute to and adhere to our governance, experimentation, model quality, versioning, observability, and compliance practices in a regulated environment

Senior AI Engineer

LLM Engineer

• You develop technically sound AI solutions for chatbots, retrieval systems and agentic workflows, deploy them to production and continuously improve them.
• You design and operate RAG architectures to answer regulatory questions based on internal and external knowledge sources, maintaining and optimizing them.
• Designing retrieval strategies, data preparation, chunking, metadata models and re-ranking methods are also part of your responsibilities.
• You build robust interfaces to data sources, knowledge stores and surrounding systems as well as prompt strategies, guardrails and agentic processes to ensure reliable and traceable responses.
• You ensure answer quality, traceability, reproducibility and reliability of AI systems and establish appropriate operational, monitoring and observability concepts for productive AI applications.
• You take on functional and technical co-responsibility for the stable, secure and auditable operation of productive AI applications.
• You analyze and resolve quality issues, hallucinations, retrieval weaknesses or misbehaviour in agentic processes — taking regulatory, data protection and security-relevant requirements into account during development and operation.

Senior AI Engineer – Generative AI, RAG, agentic systems

• You identify innovative AI use cases and support their implementation — from technical conception through to realization.
• You develop and implement tailored agentic AI solutions for various industries based on the Azure cloud.
• You build scalable platforms that enable autonomous workflows and intelligent decision-making with AI agents, and ensure their continuous development.
• You support our clients in optimizing existing AI solutions and ensure their ongoing improvement.
• You work closely with interdisciplinary teams and keep your technical knowledge up to date to continuously advance our AI solutions.

AI Engineer – Germany

• You will manage the AI roadmap and progressively transfer external expertise into a robust in-house structure.
• You will identify and prioritize use cases across the value chain, develop concepts, and support them organizationally and technically through to successful go-live.
• You will independently implement initial iterations, integrate APIs, and verify technical feasibility together with IT.
• You will coach internal “AI champions” within the business units, reduce reluctance to engage with AI, and establish a sustainable training program for the entire workforce.
• You will define clear KPIs (such as user adoption and time savings) and track the measurable business impact of your projects.

AI Implementation Lead

• You’ll join the Agentic Ants team as our second native AI engineer.
• You’ll build and extend our agentic systems alongside the rest of the team — new tools, sub-agents, prompt iterations — and co-own the evaluation framework that gates every change: golden datasets, LLM-as-judge pipelines, regression suites, production-trace mining.
• Work across both Synera MAS and Synera Assistant, picking up reliability concerns (error handling, retries) as they show up in your work.
• Partnering with the wider engineering team, help the team go deeper on customer insights data.
• Kick off sprint planning, review traces, flag failure modes, work on datasets, join team syncs, integrate CI, pair with engineers, review outputs, refine rubrics, share findings.

• Du konzipierst und baust AI-Systeme von der Architektur bis ins Deployment, mit Fokus auf LLM-Anwendungen, RAG und Agentic Workflows.
• Du entwickelst skalierbare Backend-Services und APIs in Python, meistens mit FastAPI.
• Du bringst Cloud-AI-Services in Produktion, bevorzugt auf Microsoft Azure, je nach Projekt auch AWS oder GCP.
• Du sicherst Qualität durch Tests, Evaluation und Monitoring von Anfang an.
• Du redest direkt mit Kund:innen, übersetzt fachliche Anforderungen in technische Architektur und triffst Entscheidungen im Projekt.

Senior AI Engineer w/d/m

• Build core ML systems for a proactive AI product
• Own work end-to-end: data preparation, training, evaluation, inference, and iteration
• Turn research ideas into production systems
• Debug model failures using production signals
• Collaborate with research, product, and engineering teams
• Mentor other ML engineers
• Work under production constraints

Senior Machine Learning Engineer

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability, and safety

Member of Technical Staff, Machine Learning

• You are responsible for the complete new-business cycle in the DACH region — with a clear focus on acquiring new customers (new logos): you take end-to-end ownership of sales — from the initial outreach to closing.
• You build a robust pipeline in your target segment and develop your business case for top accounts.
• You accurately identify high-revenue potential, prioritize your focus, and consistently work toward your goals.
• You win new logos.
• You lead C-level conversations (Business & IT), develop compelling value propositions, and orchestrate decision-making processes involving multiple stakeholders.
• You prepare and deliver sales pitches, presentations, and product demos together with presales and specialist teams.
• You work closely with field marketing, the SDR team, partners, and the leadership team to strategically develop your named accounts.
• You are responsible for forecasting, pipeline management, and achieving targets.
• In short: You are the hunter who will play a key role in shaping our growth in the DACH region.

Account Executive – AI, CRM, BPM, No-Code SaaS Platform

• Build LLM-based applications.
• Develop conversational systems and semantic search and integrate them into the domain-specific applications of the industry solution.
• Set up and maintain RAG (Retrieval-Augmented Generation) systems.
• Including knowledge-base management: indexing, updates, and clean, source-separated storage of structured and unstructured content.
• Operation and monitoring.
• MLOps in production: observability, structured logging, and error analysis.
• Ensure systems run reliably in production, not just that they worked once.
• Deploy agents into production.
• From development through integration and connection to portal systems to stable delivery.
• Improve solutions based on data.
• Use monitoring data, tests, and user feedback to iteratively improve solutions.
• Experiment with new approaches.
• Identify new AI use cases, prototype them, and build data pipelines from preprocessing and model development to production.

Machine Learning Engineer – m/f/d

• You translate requirements from business units into concrete, implementable AI solutions, working closely with Business, Security & Engineering.
• You take use cases from the initial idea to production — including implementation, alignment, documentation and transparency.
• You integrate AI / LLMs and agents into production workflows and contribute to building a central AI infrastructure/platform.
• You work hands-on with our enterprise AI tools (Claude Enterprise, ChatGPT Enterprise) and help to further develop them and improve usability.
• You build and maintain workflows and automations in n8n and support teams in using them independently.
• You evaluate and introduce new AI tools, consolidate existing ones, and develop standards and governance together with Security (e.g., for n8n).

AI Engineer, All Genders

• Build and deliver AI solutions: Take ownership of developing delightful, high-performance AI features to help users discover, organize, and optimize access to large datasets.
• Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for the data engineering lifecycle.
• Collaborate: Work with the rest of the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems while engaging with internal data teams for dogfooding.
• Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows.
• Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
• Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

Staff AI Engineer – 2nd Horizon

• Support in the development of AI systems.
• Optimize Python code for data pipelines.
• Perform data analysis and validation using SQL.
• Assist with data modeling and automation.

Working Student in Machine Learning – Sustainability Focus

• Das Python-Backend, das unsere medizinische Echtzeit-Dokumentation in Produktion antreibt
• Live-Transkription echter Arztgespräche: Streaming-Audio, mehrere STT-Anbieter, Qualitätsüberwachung und Fallback-Mechanismen
• Unseren Applied-AI-Kern: LLM-Evaluations-Pipelines, Prompt-Optimierung, Multi-Provider-Routing und Fallback-Ketten, inklusive der Kosten- und Latenz-Abwägungen beim Betrieb von KI im großen Maßstab
• Multi-Cloud-Produktionsinfrastruktur, die das alles im klinischen Einsatz zuverlässig hält
• Greenfield-Projekte, die definieren, was unser KI-Arzt als Nächstes wird

Engineer, Applied AI Engineering & Full-Stack

• Build customer-facing and internal product features end to end.
• Develop web flows, backend APIs, admin tools, dashboards and operational systems.
• Support products across insurance, payments, savings, investing, travel and financial services.
• Work with product, design, mobile and operations teams to launch fast.
• Integrate APIs, handle data flows and improve production reliability.
• Use analytics, feedback and production issues to improve features after launch.
• Help build tools that reduce manual work and improve speed across the business.

Full Stack Software Engineer – AI Neobank App

• Build AI agents, workflows, tools and automations that solve real customer, product and operations problems.
• Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows.
• Create AI-assisted experiences for onboarding, support, KYC, risk review, CRM, operations, document handling and product intelligence.
• Work with product and engineering teams to identify what is worth building, then build it quickly and improve it in production.
• Design around real constraints: accuracy, hallucination risk, latency, cost, security, compliance and user trust.
• Turn manual processes into reliable AI-enabled systems that can scale.

Machine Learning Engineer jobs in Germany

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Machine Learning Engineer

Senior Applied AI Engineer

Lead AI Assets Manager

Senior Machine Learning Engineer, Developer Advocacy

Senior AI Engineer

Senior AI Engineer – Generative AI, RAG, agentic systems

AI Engineer – Germany

AI Implementation Lead

Senior AI Engineer

Senior AI Engineer w/d/m

Senior Machine Learning Engineer

Member of Technical Staff, Machine Learning

Account Executive – AI, CRM, BPM, No-Code SaaS Platform

Machine Learning Engineer – m/f/d

AI Engineer, All Genders

Staff AI Engineer – 2nd Horizon

Working Student in Machine Learning – Sustainability Focus

Engineer, Applied AI Engineering & Full-Stack

Full Stack Software Engineer – AI Neobank App

Applied AI Engineer