Scale’s rapidly growing International 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 custom LLMs
• Upskilling and advisory services to spread the impact of AI

As a Full Stack Software Engineer (Forward Deployed), you’ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens.

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:

• Serve as the lead technical strategist for public sector engagements, converting ambiguous mission requirements into robust architectural roadmaps and guiding onsite implementation
• Architect the fundamental frameworks for production-grade AI applications, setting the gold standard for how interactive UIs, backend systems, and AI models are integrated at scale to deliver reliable outcomes.
• Guide the evolution of cloud infrastructure, ensuring security, global scalability, and long-term system integrity across all environments.
• Direct the development of core platforms and shared services, ensuring they solve cross-cutting needs for diverse global client use cases.
• Partner with cross-functional leadership to steer the technical roadmap, mentoring senior and junior staff and ensuring all products align with a cohesive, future-proof technical architecture.
• Bridge the gap between the field and the core platform by turning real-world client lessons into the reusable patterns that power the entire engineering team.

Ideally you’d have:

• Masters or Phd in Computer Science or equivalent deep industry experience in architecting complex, distributed systems.
• 10+ years of full-stack expertise across Python, Node.js, and React, with a proven track record of designing high-scale architectures on Kubernetes and global cloud infrastructures (AWS/Azure/GCP).
• Expert ability to design and oversee production-grade ecosystems, ensuring world-class standards for system integrity, security, and long-term scalability.
• Extensive experience deploying and troubleshooting sophisticated end-to-end solutions directly within complex, high-security client environments.
• A self-driven leader capable of resolving extreme ambiguity, mentoring senior staff, and setting the technical vision for the organization.
• A driver of asynchronous workflows and documentation-first cultures to streamline global engineering velocity and reduce friction.
• Proficient in Arabic

Nice to haves:

• Past experience working at a startup as a CTO or founding engineer or in a forward deployed engineer / dedicated customer engineer role
• Experience working cross functionally with operations
• Proven track record of building LLM-driven solutions with the strategic foresight to anticipate landscape shifts and architect future-proof systems.

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.

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.