
Jobgether
AI/ML & Forward Deployed Engineer
Die Rolle als AI/ML & Forward Deployed Engineer in Deutschland umfasst die Entwicklung und den Betrieb von KI-, Machine-Learning- und GenAI-Lösungen von der Konzeption bis zur Produktion. Der Fokus liegt auf skalierbaren, sicheren und zuverlässigen AI-Produkten sowie der Zusammenarbeit mit Stakehol…
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Stellenbeschreibung
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI/ML & Forward Deployed Engineer based in Germany.
This role offers the opportunity to build and deploy high-impact AI, machine learning, and generative AI solutions from initial concept through production.
You will combine software engineering, machine learning, and MLOps/LLMOps expertise to create scalable and reliable AI products.
The position involves solving complex business problems through technologies such as LLMs, RAG pipelines, NLP, forecasting, and anomaly detection.
You will work across the full AI lifecycle, from experimentation and evaluation to deployment, monitoring, and continuous improvement.
Strong attention to security, governance, observability, and data quality will be essential when delivering production-ready solutions.
You will also collaborate closely with stakeholders to translate business needs into practical technical solutions and measurable outcomes.
This is an excellent opportunity for an experienced engineer who enjoys combining advanced AI technologies with hands-on implementation and real-world impact.
Accountabilities
- Design, develop, and deploy machine learning, AI, and GenAI solutions from proof of concept through production.
- Build and optimize ML models and applications covering deep learning, NLP, forecasting, classification, regression, and anomaly detection use cases.
- Develop production-grade GenAI applications using LLMs, RAG pipelines, embeddings, retrieval optimization, reranking, and prompt engineering.
- Design and implement AI evaluation frameworks to assess model quality, reliability, relevance, and performance.
- Build scalable AI services and integrations using REST and gRPC APIs as well as event-driven architectures.
- Establish and maintain MLOps and LLMOps practices covering deployment, automation, versioning, monitoring, and lifecycle management.
- Containerize and orchestrate AI applications using Docker and Kubernetes and integrate them into robust CI/CD pipelines.
- Implement model monitoring, drift detection, performance tracking, and processes for continuous model improvement.
- Ensure AI solutions meet enterprise requirements for data quality, governance, security, role-based access control, encryption, and auditability.
- Collaborate with business and technical stakeholders to understand requirements, identify opportunities for AI adoption, and translate them into effective technical solutions.
- Support solutions through production operations, troubleshooting, optimization, and ongoing improvements.
- Apply strong engineering practices to ensure AI systems are scalable, secure, observable, maintainable, and aligned with business objectives.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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