Jakarta, Jakarta, Indonesia
Open 6 months, first seen by us 203 days agoEmployment type in the employer’s posting: Full-timeFrom the employer’s posting
Design and deploy AI solutions (ML, LLMs, generative AI) for client business needs
Advise client stakeholders on technical architecture and AI best practices
Build PoCs and move them into production-ready environments
Design AI infrastructure on AWS, Azure, or GCP with data pipelines
Lead project workstreams and mentor junior engineers on MLOps and coding
Design, implement, and deploy pragmatic AI solutions (ML, LLMs, Generative AI) tailored to specific client business needs.
Act as a technical advisor to client stakeholders, translating business requirements into scalable technical architectures
Build and test Proof of Concepts (PoCs) and transition them into production-ready environments
Design robust AI infrastructure using cloud-native services (AWS, Azure, or GCP) and modern data pipelines.
Lead project workstreams and mentor junior engineers on technical best practices, MLOps, and coding standards.
Experience: 5+ years in Software Engineering, Data Science, or AI/ML development.
Communication: Fluency in English and the local regional language (German or French). Ability to explain complex technical concepts to non-technical business leaders.
Qualifications & Soft Skills - Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related STEM field. - Communication: Fluency in English and the local regional language (German or French). Ability to explain complex technical concepts to non-technical business leaders.
Open 6 monthsWe first saw this posting 203 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 203
Up longer than most. Similar jobs usually come down between day 6 and day 70.
Well past Artefact’s usual: its jobs come down by about day 36.
From 4,504 similar postings that came down, and 27 of Artefact’s. Coming down is not always a hire.
46 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Experience: 5+ years in Software Engineering, Data Science, or AI/ML development. - Core Programming: Mastery of Python and SQL; familiarity with other languages (Java, C++, or Node.js) is a plus. - AI/ML Frameworks: Deep experience with TensorFlow, PyTorch, or HuggingFace.
- Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning). - Data Engineering: Ability to build and manage ETL/ELT pipelines and work with various database schemas (SQL, NoSQL, Graph). Qualifications & Soft Skills
- Prototyping & Production: Build and test Proof of Concepts (PoCs) and transition them into production-ready environments, ensuring security, performance, and maintainability. - Architecture & Infrastructure: Design robust AI infrastructure using cloud-native services (AWS, Azure, or GCP) and modern data pipelines. - Collaboration: Work within cross-functional teams (Data Scientists, Project Managers, and Strategy Consultants) to ensure the technical feasibility of AI initiatives.
- Generative AI: Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings. - Cloud Platforms: Proven experience deploying AI solutions on AWS, GCP, or Azure. - Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning).
- Cloud Platforms: Proven experience deploying AI solutions on AWS, GCP, or Azure. - Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning). - Data Engineering: Ability to build and manage ETL/ELT pipelines and work with various database schemas (SQL, NoSQL, Graph).
- Core Programming: Mastery of Python and SQL; familiarity with other languages (Java, C++, or Node.js) is a plus. - AI/ML Frameworks: Deep experience with TensorFlow, PyTorch, or HuggingFace. - Generative AI: Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
What you will be doing?
We are looking for a Senior AI Engineer / Technical Consultant to bridge the gap between high-level strategy and technical execution. You will act as a "builder first, consultant second," designing and deploying AI/ML solutions that solve complex business problems for global clients. This role involves end-to-end technical leadership, from initial rapid prototyping (PoCs) to scaling production-ready systems.
Solution Engineering: Design, implement, and deploy pragmatic AI solutions (ML, LLMs, Generative AI) tailored to specific client business needs.
Technical Consulting: Act as a technical advisor to client stakeholders, translating business requirements into scalable technical architectures and guiding them on AI best practices.
Prototyping & Production: Build and test Proof of Concepts (PoCs) and transition them into production-ready environments, ensuring security, performance, and maintainability.
Architecture & Infrastructure: Design robust AI infrastructure using cloud-native services (AWS, Azure, or GCP) and modern data pipelines.
Collaboration: Work within cross-functional teams (Data Scientists, Project Managers, and Strategy Consultants) to ensure the technical feasibility of AI initiatives.
Mentorship: Lead project workstreams and mentor junior engineers on technical best practices, MLOps, and coding standards.
Experience: 5+ years in Software Engineering, Data Science, or AI/ML development.
Core Programming: Mastery of Python and SQL; familiarity with other languages (Java, C++, or Node.js) is a plus.
AI/ML Frameworks: Deep experience with TensorFlow, PyTorch, or HuggingFace.
Generative AI: Hands-on experience with LLMs, prompt engineering, fine-tuning, and vector embeddings.
Cloud Platforms: Proven experience deploying AI solutions on AWS, GCP, or Azure.
Tools & DevOps: Proficiency with Git, Docker, Kubernetes, and MLOps principles (CI/CD for machine learning).
Data Engineering: Ability to build and manage ETL/ELT pipelines and work with various database schemas (SQL, NoSQL, Graph).
Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related STEM field.
Communication: Fluency in English and the local regional language (German or French). Ability to explain complex technical concepts to non-technical business leaders.
Mindset: A "builder’s mindset" with the agility to work in a fast-paced, client-facing consulting environment.
Consulting Experience: Prior experience in a professional services or consulting firm is highly preferred.
Impactful work on global accounts (e.g., Warner Bros, Orange, L'Oréal).
A collaborative "scale-up" environment with a heavy focus on continuous learning and a dedicated training budget.
Opportunity to lead high-visibility projects within the first year.
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Jakarta, Jakarta, Indonesia
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