Machine Learning Engineer

Scarlet

. Build agentic document-understanding systems that search, parse and visually inspect technical files .

Posted 10/3/2026full-timeLondon • United KingdomMid-LevelSenior💰 £90,000 - £150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying document-understanding systems and machine learning evaluation datasets, with a strong focus on accuracy, security, and user understanding. Capable of collaborating with cross-functional teams to enhance medical-device certification processes while ensuring safety and compliance.

Highest-signal resume keywords

Machine Learning Systems OwnershipDocument-Understanding Systems DevelopmentDeep Learning and Information RetrievalProduction System Design and DeploymentDataset Creation for ML Evaluation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningInformation RetrievalStatisticsDataset BuildingProduction System DeploymentContext ManagementEvaluation MetricsAgent ToolsPragmatic Security Judgment

Soft Skills

CollaborationProblem SolvingCommunication

Industry Keywords

Medical-Device CertificationDocument CollectionsSource AttributionUser UnderstandingImpartiality and Objectivity

About the role

Key responsibilities & impact

Build agentic document-understanding systems that search, parse and visually inspect technical files
Develop agent harnesses to retrieve information across large document collections in varied formats
Preserve source attribution and minimise hallucination while balancing accuracy, latency and cost
Deploy agent systems to production
Define success with assessors and build datasets and benchmarks for a complex domain
Measure retrieval quality, citation correctness, expert agreement, assessor effort, assessment quality, customer experience and rework
Use evaluation results to prioritise improvements
Build agents that respect the impartiality and objectivity required of a certification body
Help users understand evidence, recognise uncertainty and retain responsibility for consequential judgments
Own ML systems from conception and prototyping through deployment, evaluation and iterative improvement
Collaborate with clinicians, assessors and engineers to accelerate medical-device certification without compromising safety

Requirements

What you’ll need

3+ years shipping software to production
Understanding of deep learning, agent tools, context management and information retrieval
Experience building datasets for machine learning evaluation
First-principles understanding of statistics and evaluating ML systems
Experience designing, deploying and operating production systems
Pragmatic production security judgment covering data access, permissions, untrusted inputs and consequential actions
Ability to choose infrastructure appropriate to workload and explain trade-offs in complexity, reliability, security and cost
Ability to own ambiguous problems from defining success with domain experts through experiments and production improvement
Experience deploying agent systems with tool use, sensitive data or consequential actions, including evaluation and safeguards (preferred)
Experience building retrieval or document-understanding systems whose outputs must be checked against complex source evidence (preferred)
Ability to work in the London office for the working session

Benefits

Comp & perks

Equity
Working session and interviews as part of the hiring process