About the Role

<h2 data-start="107" data-end="126">Who is Artefact?</h2> 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. <h2 data-start="797" data-end="821">Main Responsibilities</h2> 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. <ul data-start="1098" data-end="2600"> <li data-start="1098" data-end="1326"> 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. </li> <li data-start="1327" data-end="1512"> 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. </li> <li data-start="1513" data-end="1754"> 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. </li> <li data-start="1755" data-end="1927"> Cloud & MLOps/LLMOps: Design and operate solutions on Azure, GCP, or AWS (CI/CD, containers, model serving, feature stores, vector DBs, monitoring, eval pipelines). </li> <li data-start="1928" data-end="2127"> Client advisory & stakeholder management: Translate business goals into technical roadmaps, present to senior stakeholders, manage risks and trade-offs, and ensure measurable business impact. </li> <li data-start="2128" data-end="2265"> Quality, security & governance: Enforce best practices on data privacy, model risk management, responsible AI, and documentation. </li> <li data-start="2266" data-end="2425"> Team leadership & mentoring: Coach engineers/consultants, perform code and design reviews, and help shape delivery standards and reusable accelerators. </li> <li data-start="2426" data-end="2600"> Pre-sales & thought leadership: Support proposals, estimates, and statements of work; contribute to assets, talks, and publications that advance Artefact’s AI offering. </li> </ul> <h2 data-start="2602" data-end="2622">Candidate Profile</h2> Engineer first, consultant second — with a builder’s mindset and a track record of shipping. <ul data-start="2717" data-end="3945"> <li data-start="2717" data-end="2874"> Experience: 5–8+ years in data/ML/AI engineering or adjacent roles, including end-to-end delivery of production AI systems (not just prototypes). </li> <li data-start="2875" data-end="3010"> Programming: Expert Python; solid software engineering (testing, packaging, CI/CD). SQL required; Java/Scala/TypeScript a plus. </li> <li data-start="3011" data-end="3145"> AI/ML: Hands-on with ML/DL and LLMs (prompting, fine-tuning/LoRA, embeddings/RAG, evaluation & observability, guardrails). </li> <li data-start="3146" data-end="3266"> Cloud: Deep experience on at least one major cloud (Azure, GCP, or AWS) deploying secure, scalable services. </li> <li data-start="3267" data-end="3504"> MLOps/LLMOps: 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). </li> <li data-start="3505" data-end="3640"> Architecture & data: Designing data/ML platforms, APIs, microservices; familiarity with data pipelines and streaming is valued. </li> <li data-start="3641" data-end="3761"> Consulting skills: Requirements gathering, storytelling, senior stakeholder management, and clear documentation. </li> <li data-start="3762" data-end="3876"> Languages: Fluency in French and English (written & spoken). </li> <li data-start="3877" data-end="3945"> Work eligibility: You must be eligible to work in Switzerland. </li> </ul> Nice to have <ul data-start="3964" data-end="4225"> <li data-start="3964" data-end="4062"> Experience with responsible AI/governance frameworks, security reviews, and cost optimization. </li> <li data-start="4063" data-end="4158"> Domain experience in one or more industries (e.g., retail, pharma, manufacturing, finance). </li> <li data-start="4159" data-end="4225"> Contributions to open-source, publications, or conference talks. </li> </ul> <h2 data-start="4227" data-end="4241">Why Join Us</h2> <ul data-start="4242" data-end="4752"> <li data-start="4242" data-end="4359"> Strategy with a Data Edge: Operate at the intersection of boardroom strategy and cutting-edge AI engineering. </li> <li data-start="4360" data-end="4494"> Romandie Office Impact: High visibility from day one; help shape our Swiss footprint and work directly with senior leadership. </li> <li data-start="4495" data-end="4630"> Learning & Growth: Advanced training across strategy, AI/ML/LLM, and cloud; international missions and communities of practice. </li> <li data-start="4631" data-end="4752"> Culture of Doers: Innovation, action, collaboration. We move fast, deliver impact, and support each other’s growth. </li> </ul> Location: Lausanne / Geneva (Romandie) If you don’t meet 100% of the criteria, we still want to hear from you. Passion, curiosity, and impact orientation matter — tell us about yours.

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Senior AI Engineer / Technical Consultant

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