1 day ago

Staff Applied AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Drive how AI is built, governed, and evaluated for the Global Public Sector team. Define standards for responsible AI, model governance, and production MLOps, and build or validate the highest-risk components of strategic AI systems. Architect failure-resistant AI, lead resolution of severe safety or data-integrity incidents, create reusable agent and evaluation capabilities, and advise clients on what to adopt while coaching senior engineers.

Location: London

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Define standards for responsible AI, model governance, and production MLOps across the Global Public Sector team
•Build or validate the highest-risk parts of strategic AI systems to establish broadly adoptable standards
•Architect AI systems to prevent systemic failure and lead resolution of severe incidents related to model safety or data integrity
•Create reusable production AI capabilities (agent implementations, fine-tuned models, and evaluation methodologies) for engineers and clients
•Advise on which AI developments to adopt, set the technical roadmap, and act as a senior technical partner to client leadership

Key Requirements

•7+ years of engineering experience owning AI/ML systems in production
•Experience evaluating training data, selecting adaptation methods, assessing fine-tuning results, and balancing serving cost, latency, and quality
•Experience owning an AI-powered product end to end, including direct involvement in AI behavior
•Track record establishing standards that outlast projects (e.g., evaluation methodology, MLOps practice, or architectural pattern)
•Comfort working with executive-level clients and leadership, including defending technical positions under pressure

Experience:AI/MLMLOpsPublic sectorRegulated AIOn-premise AI

Skills:Defining standardsTechnical leadershipIncident resolutionCoachingClient advisory

Languages:English

Company Brief

Scale AI

Provides data labeling, annotation, and infrastructure services to accelerate machine learning and AI development. Supplies high-quality training data, tooling, and APIs for customers in autonomous vehicles, mapping, robotics, and enterprise AI applications.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2016

Website LinkedIn

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Scale AI

1 day ago

Staff Applied AI Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Location: London

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Define standards for responsible AI, model governance, and production MLOps across the Global Public Sector team
•Build or validate the highest-risk parts of strategic AI systems to establish broadly adoptable standards
•Architect AI systems to prevent systemic failure and lead resolution of severe incidents related to model safety or data integrity
•Create reusable production AI capabilities (agent implementations, fine-tuned models, and evaluation methodologies) for engineers and clients
•Advise on which AI developments to adopt, set the technical roadmap, and act as a senior technical partner to client leadership

Key Requirements

•7+ years of engineering experience owning AI/ML systems in production
•Experience evaluating training data, selecting adaptation methods, assessing fine-tuning results, and balancing serving cost, latency, and quality
•Experience owning an AI-powered product end to end, including direct involvement in AI behavior
•Track record establishing standards that outlast projects (e.g., evaluation methodology, MLOps practice, or architectural pattern)
•Comfort working with executive-level clients and leadership, including defending technical positions under pressure

Experience:AI/MLMLOpsPublic sectorRegulated AIOn-premise AI

Skills:Defining standardsTechnical leadershipIncident resolutionCoachingClient advisory

Languages:English

Company Brief

Scale AI

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2016

Website LinkedIn