Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.
The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner…

What you will be doing?
As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data.

Your responsibilities will include:

• Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms.
• Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions.
• Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions.
• Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing.
• Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics.

What we are looking for?

• 2-5 years: Data Engineer
• Proficiency in Python, SQL, and database management.
• Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka.
• Proven problem-solving skills and a solution-oriented mindset.
• Experience working with business stakeholders either internally or externally
• Excellent communication skills to collaborate effectively within teams and with stakeholders.
• Strong business acumen with an interest in business-facing roles.
• Adaptability and a start-up mentality to thrive in a dynamic environment.
• Minimum of a bachelor's degree in Computer Science, Electronics, and Communication Engineering degrees.

Artefact is the place to be: come and build the future of data and AI

Innovation: We have a passion for creating impacting projects and believe innovation can come from anyone.
Action: We make things rather than telling people how to make them.
Collaboration: We believe in bringing talented people together, winning together, and in learning from each other.

Role Overview

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of:

• Creating custom AI applications that will impact millions of citizens
• Generating high-quality training data for national LLMs
• Upskilling and advisory services to spread the impact of AI

As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.

At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you.

You will:

• Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies.
• Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment.
• Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability.
• Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks.
• Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again.
• Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials.
• Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases.

Ideally, you have:

• Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector.
• Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI.
• System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core.
• Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools.
• Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them.
• Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy.
• Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it.

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of:

• Creating custom AI applications that will impact millions of citizens
• Generating high-quality training data for national LLMs
• Upskilling and advisory services to spread the impact of AI

We are hiring Applied AI Engineers to build custom end-to-end AI applications for our public sector clients using the latest developments in the field of AI. You will also get the opportunity to develop and be part of creating custom datasets, evaluations, and fine-tuning these sophisticated models to maximize performance and apply on real world use cases with global reach. 

At Scale, we’re not just building AI solutions—we are building repeatable blocks to enable the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a member of our rapidly expanding team, we’d love to hear from you.

You will:

• Partner with public sector clients to deeply understand their challenges and define AI-driven solutions 
• Build and deploy end-to-end AI applications into production leveraging latest developments from the biggest AI labs, and open source models
• Collaborate with cross-functional teams, including data annotation specialists, to create high-quality training datasets
• Design and maintain robust evaluation frameworks to ensure the reliability and effectiveness of AI models
• Participate in customer engagements, including occasional travel (approximately two weeks per quarter)
• Contribute to the scaling of AI capabilities in the public sector through hands-on knowledge sharing

Ideally you’d have:

• A strong engineering background, with a Bachelor’s degree in Computer Science, Mathematics, or a related quantitative field (or equivalent practical experience)
• 7+ years of post-graduation engineering experience, with demonstrated proficiency in languages such as Python, TypeScript/JavaScript, Java, or C++.
• 2+ years of experience applying AI/ML in production environments, such as deploying deep learning solutions, building generative/agentic AI applications or setting up evaluations pipelines
• Familiarity with cloud-based machine learning tools and platforms (e.g. AWS, GCP, Azure)
• Strong problem-solving skills, with a data-driven approach to iterating on machine learning models and datasets
• Excellent written and verbal communication skills to collaborate effectively in a cross-functional environment

Nice to haves:

• Experience working at a startup, particularly as founding engineer
• Experience building and deploying large-scale AI solutions
• Strong written and verbal communication skills to operate in a cross-functional team environment
• Proficiency in Arabic (if focused on language models)

Scale’s mission is to develop reliable AI systems for the world's most important decisions. Our core work consists of:

• Creating custom AI applications that will impact millions of citizens
• Generating high-quality training data for national LLMs
• Upskilling and advisory services to spread the impact of AI

Scale is hiring ML Research Engineers to bridge the gap between frontier research and real-world impact. While we solve critical challenges for global governments, your role will extend beyond implementation. You will lead the charge in research into Agent design, Deep Research and AI Safety/reliability, developing novel methodologies that not only power public sector applications but set new standards across the entire Scale organisation.

Your mission is threefold:

• Frontier Research & Publication: Leading research into LLM/agent capabilities, reasoning, and safety, with the goal of publishing at top-tier venues (NeurIPS, ICML, ICLR).
• Cross-Org Impact: Developing generalised techniques in Agent design, AI Safety and Deep Research agents that scale across our commercial and government platforms.
• Mission-Critical Applications: Engineering high-stakes AI systems that impact millions of citizens globally.

You will:

• Pioneer Novel Architectures: Design and train state-of-the-art models and agents, moving beyond “off-the-shelf” solutions to create custom architectures for complex public sector reasoning tasks.
• Lead AI Safety Initiatives: Research and implement robust safety frameworks, including red teaming, alignment (RLHF/DPO), and bias mitigation strategies essential for sovereign AI.
• Drive Deep Research Capabilities: Develop agents capable of long-horizon reasoning and autonomous information synthesis to solve complex problems for national security and public policy.
• Publish and Contribute: Represent Scale in the broader research community by publishing high-impact papers and contributing to open-source breakthroughs.
• Consult as a Subject Matter Expert: Act as a technical authority for public sector leaders, advising on the theoretical limits and safety requirements of emerging AI.
• Build Evaluation Frontiers: Create new benchmarks and evaluation protocols that define what success looks like for high-stakes, non-commercial AI applications.

Ideally, you’d have:

• Advanced Degree: PhD or Master’s in Computer Science, Mathematics, or a related field with a focus on Deep Learning.
• Research Track Record: A portfolio of first-author publications at major conferences (NeurIPS, ICML, CVPR, EMNLP, etc.).
• Engineering Rigour: Strong proficiency in Python, deep learning frameworks (PyTorch/JAX), with the ability to write production-ready code that scales.
• Safety Expertise: Experience in alignment, robustness, or interpretability research.

Nice to haves:

• Experience with large-scale distributed training on massive clusters.
• Experience in building agentic systems that are reliable.
• Experience in Sovereign AI or working with highly regulated data environments.
• A zero-to-one mindset: Comfortable navigating ambiguity and defining research directions from scratch.

Role Overview

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of:

• Creating custom AI applications that will impact millions of citizens
• Generating high-quality training data for national LLMs
• Upskilling and advisory services to spread the impact of AI

As a Principal AI Ops Architect, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.

At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you.

You will:

• Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies.
• Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment.
• Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability.
• Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks.
• Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again.
• Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials.
• Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases.

Ideally, you have:

• Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector.
• Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI.
• System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core.
• Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools.
• Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them.
• Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy.
• Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it.