2 months ago
Jakarta, IndonesiaSenior
Responsibilities
- Design, implement, and deploy pragmatic ML, LLM, and generative AI solutions tailored to client business needs.
- Translate business requirements into scalable technical architectures and advise client stakeholders on AI best practices.
- Build and test proofs of concept and transition them into secure, performant, maintainable production environments.
- Design AI infrastructure using AWS, Azure, or GCP and build modern data pipelines.
- Collaborate with data scientists, project managers, and strategy consultants on AI initiatives.
- Lead project workstreams and mentor junior engineers on technical practices, MLOps, and coding standards.
Requirements
- 5+ years of experience in software engineering, data science, or AI/ML development.
- Mastery of Python and SQL; familiarity with Java, C++, or Node.js is a plus.
- Deep experience with TensorFlow, PyTorch, or HuggingFace.
- Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings.
- Experience deploying AI solutions on AWS, GCP, or Azure.
- Proficiency with Git, Docker, Kubernetes, and MLOps principles.
- Ability to build and manage ETL/ELT pipelines and work with SQL, NoSQL, and graph database schemas.
- Bachelor’s or master’s degree in computer science, data science, engineering, or a related STEM field.
- Fluency in English and German or French, with the ability to explain technical concepts to non-technical business leaders.
- Professional services or consulting experience is highly preferred.
- Ability to work in a fast-paced, client-facing consulting environment with a builder’s mindset.
Benefits
- Impactful work on global accounts and high-visibility projects.
- Collaborative scale-up environment focused on continuous learning.
- Dedicated training budget.
- Opportunity to lead high-visibility projects within the first year.
Categories
Solutions Engineering
About Artefact
Artefact is a Paris‑headquartered consulting and engineering firm that builds data and AI solutions for large enterprises, from strategy and governance to platforms, MLOps, and data‑driven marketing. It operates across 27 countries and works with brands such as L’Oréal and Sanofi. The company is privately held and monetizes through consulting engagements, industrialized AI projects, and managed data services.