Hands-on with ML/DL and LLMs (prompting, fine-tuning/LoRA, embeddings/RAG, evaluation & observability, guardrails)
Deep experience on at least one major cloud (Azure, GCP, or AWS) deploying secure, scalable services
Containers (Docker/Kubernetes), Git, pipelines (e.g., GitHub Actions/Cloud-native), model serving (FastAPI/TorchServe/Triton), experiment tracking, model registry, vector DBs (FAISS, Pinecone, pgvector, OpenSearch)
Designing data/ML platforms, APIs, microservices; familiarity with data pipelines and streaming is valued
Requirements gathering, storytelling, senior stakeholder management, and clear documentation
Fluency in French and English (written & spoken)
Nice to have4
Java/Scala/TypeScript a plus
Experience with responsible AI/governance frameworks, security reviews, and cost optimization
Domain experience in one or more industries (e.g., retail, pharma, manufacturing, finance)
Contributions to open-source, publications, or conference talks
Eligibility1
You must be eligible to work in Switzerland
Skills
Python
PyTorch
TensorFlow
HuggingFace
LangChain
LlamaIndex
Azure
GCP
AWS
Docker
Kubernetes
Git
GitHub Actions
FastAPI
TorchServe
Triton
FAISS
Pinecone
pgvector
OpenSearch
SQL
Who is Artefact?
Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact.
With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.
Main Responsibilities
As a Senior Technical Consultant / Senior AI Engineer, you will lead the design and delivery of impactful AI and data solutions. You’ll combine hands-on engineering with client advisory, guiding multi-disciplinary teams from opportunity framing to production deployment.
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Own solution architecture & delivery: Define end-to-end architectures (data, ML/LLM, APIs, security), make build/buy decisions, and drive projects from PoC to production with reliability, observability, and cost in mind.
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Lead complex PoCs & pilots: Scope, prototype, and validate AI/ML use cases (incl. LLMs/GenAI, RAG, fine-tuning, evaluation) and convert successful pilots into scalable products.
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Advanced programming & modeling: Build, adapt, and evaluate ML/DL/LLM models using Python (PyTorch, TensorFlow, HuggingFace, LangChain/LlamaIndex), including prompt engineering, fine-tuning/LoRA, vector search, and safety/guardrails.
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Cloud & MLOps/LLMOps: Design and operate solutions on Azure, GCP, or AWS (CI/CD, containers, model serving, feature stores, vector DBs, monitoring, eval pipelines).
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Client advisory & stakeholder management: Translate business goals into technical roadmaps, present to senior stakeholders, manage risks and trade-offs, and ensure measurable business impact.
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Quality, security & governance: Enforce best practices on data privacy, model risk management, responsible AI, and documentation.
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Team leadership & mentoring: Coach engineers/consultants, perform code and design reviews, and help shape delivery standards and reusable accelerators.
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Pre-sales & thought leadership: Support proposals, estimates, and statements of work; contribute to assets, talks, and publications that advance Artefact’s AI offering.
Candidate Profile
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
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Experience: 5–8+ years in data/ML/AI engineering or adjacent roles, including end-to-end delivery of production AI systems (not just prototypes).