Senior AI/ML Engineer, CH

Darum lohnt es sich

The role is primarily based in Zurich, with occasional travel to client sites and collaboration with teams across Europe.

Apply software engineering best practices (testing, CI/CD, modular design, documentation) Collaborate with cross‑functional teams (data engineers, MLOps, cloud architects, and business stakeholders) Solve real‑world enterprise challenges (security, compliance, legacy system integration) Own the full lifecycle of AI models, from data exploration to production monitoring Job Requirements 5+ years of experience in AI/ML engineering, software development, or a related field Expertise in LLM architectures and training methodologies: Transformers, attention mechanisms, fine‑tuning, RAG, quantization Prompt engineering, model evaluation, bias detection Strong knowledge of machine learning architectures: fully connected, CNN, LSTM, transformers and classical ML models Strong software engineering skills: Proficient in Python (FastAPI, Pydantic, asyncio, type hints) Experience with API development Familiarity with modern toolchains (Docker, Kubernetes, Terraform) Hands‑on experience with LLM integrations: LLM providers Vector databases (Pinecone, Weaviate, Milvus) Model serving (vLLM, TGI, KServe) Experience with MLOps and production deployments Understanding of enterprise challenges: Security, compliance, scalability, cost optimization.

Job Description As a Senior AI/ML Engineer at vector8, you will design, implement, and deploy AI solutions that bridge the gap between research and production. Your work will focus on integrating and fine‑tuning AI models, optimizing model performance, and ensuring enterprise‑grade reliability, security, and scalability.

This Is a Hands‑on Engineering Role Where You Will Develop and optimize LLM and VLM‑powered solutions for enterprise use cases Develop and optimize TTS, STT and ML models.

Experience with relational and non‑relational databases Strong problem‑solving and debugging skills Excellent communication and collaboration skills (fluent in English; German is a strong plus) Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related field Experience with multi‑cloud environments (AWS, Azure, GCP) Experience with code optimization (e.g., model quantization, parallelization).

Job Responsibilities End‑to‑End Model Development Design, implement, and deploy distributed, high‑volume, high‑performance, low‑latency machine learning solutions, with a focus on GenAI models, and especially LLM integrations and API‑driven architectures Take ownership of your models throughout their entire life cycle: Data exploration and cleaning to build reproducible, versioned datasets State‑of‑the‑art research to identify the best architectures for the problem (e.g., transformers, RAG, fine‑tuning) Implementation, training, and optimization in reproducible environments Deployment, monitoring, and maintenance in production Optimize models for performance, latency, and cost efficiency, especially in LLM serving and inference Software Engineering for AI Write clean, modular, and well‑documented code in Python (FastAPI, Pydantic, asyncio) Apply best practices in: Testing (unit, integration, end‑to‑end) CI/CD (GitHub Actions, GitLab CI, ArgoCD) Observability (logging, monitoring, tracing) Ensure security and compliance (data protection, access controls, encryption) Integrate models and code into CI/CD pipelines for seamless deployment AI