Remote GenAI & ML Production Engineer

Jobgether; Schweiz; Vor Ort; CHF 80.000 - 97.000; Vollzeit

Benefits dieser Stelle

Remote work

Competitive salary

GenAI & MLOps projects exposure

Cloud-native engineering practices

Zusammenfassung

Jobgether in Switzerland is seeking an AI/ML & Forward Deployed Engineer to build and deploy high-impact AI solutions from concept to production, blending software engineering with MLOps and GenAI.

You will work across the full AI lifecycle, implementing LLMs, RAG pipelines, embeddings, and evaluation frameworks, ensuring security and governance, and collaborating with stakeholders to translate business challenges into scalable, observable systems.

Qualifikationen

• 8+ years of professional software or technical engineering experience.
• Advanced Python development and ML/DL expertise.
• Experience with NLP, forecasting, classification, regression, and anomaly detection.
• Proven GenAI application development using LLMs and RAG architectures.
• Strong knowledge of data governance, security, and RBAC.

Aufgaben

• Design, develop, and deploy ML/AI/GenAI solutions from PoC to production.
• Build scalable AI services with REST and gRPC APIs and event-driven architectures.
• Establish MLOps/LLMOps practices including monitoring and lifecycle management.
• Containerize using Docker and orchestrate with Kubernetes in CI/CD pipelines.
• Collaborate with stakeholders to translate business needs into technical solutions.

Kenntnisse

Python development

ML Engineering

GenAI

MLOps/LLMOps

NLP

LLM evaluation

Embeddings

Problem solving

Tools

Docker

Kubernetes

CI/CD

REST APIs

gRPC

Jobbeschreibung

Jobgether in Switzerland is seeking an AI/ML & Forward Deployed Engineer to build and deploy high-impact AI solutions from concept to production, blending software engineering with MLOps and GenAI.

You will work across the full AI lifecycle, implementing LLMs, RAG pipelines, embeddings, and evaluation frameworks, ensuring security and governance, and collaborating with stakeholders to translate business challenges into scalable, observable systems.