Machine Learning Engineer

Xantura Limited

Machine Learning Engineer advancing Xantura’s predictive modelling platform for housing, health, and social vulnerabilities. Deploying responsible ML systems, pipelines, APIs, and models to production.

Posted 8/20/2026full-timeLondon • 🇬🇧 United KingdomMid-LevelSenior💰 £50,000 - £70,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in predictive modeling, machine learning, and data pipeline development, with a strong focus on ethical AI deployment and continuous improvement of analytics. Proficient in Python and experienced in building scalable systems using modern orchestration and containerization tools.

Highest-signal resume keywords

Predictive ModelingMachine Learning EngineeringPython ProgrammingData Pipeline DevelopmentContainerization with Kubernetes

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive ModelingMachine LearningPython ProgrammingData Pipeline DevelopmentAPIs ImplementationEmbedding-Based ArchitecturesGradient-Boosted Decision TreesNatural Language ProcessingContainerized SystemsAsynchronous APIs

Tools & Technologies

PyTorchScikit-learnXGBoostLightGBMDagsterAirflowPrefectKubernetesAzure Kubernetes ServiceHugging Face Transformers

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s Degree in Machine LearningPhD in Computer Science

Industry Keywords

Ethical AIPredictive AnalyticsSocial DomainsOpen-Source SoftwareText Analytics

Tech Stack

Tools & technologies

AirflowAzureKubernetesPythonPyTorchScikit-LearnVault

About the role

Key responsibilities & impact

Own and advance a predictive modelling platform that scales across problem types and tenants
Design, implement, and iterate models including embedding-based sequence encoders, temporal survival models, and gradient-boosted decision trees
Predict key vulnerabilities in housing, health, and other social domains
Track developments in ML and frontier models and run structured experiments to bring promising techniques safely into production
Build robust evaluation pipelines, training datasets, and model infrastructure
Support continuous improvement of natural language and predictive analytics
Ensure responsible AI deployment by embedding ethical and regulatory considerations throughout development
Work in the Platform team responsible for deployment and evolution of the backend platform underpinning Xantura’s core business

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience
3+ years of professional experience as an ML Engineer, or related role
Strong programming skills and production experience in Python
Experience building and maintaining data or ML pipelines with an orchestration tool such as Dagster, Airflow, or Prefect
Hands-on experience with PyTorch, scikit-learn, and gradient-boosting libraries such as XGBoost or LightGBM
Practical experience defining and deploying containerised systems
Experience implementing APIs for internal services, such as FastAPI
Experience deploying containerised systems to production, particularly via Kubernetes
PhD in Computer Science, Machine Learning, or a related field with a strong publication record in text analytics, representation learning, or applied predictive modelling would be an advantage
Practical experience productionising LLMs would be an advantage
Experience with vector databases and retrieval-augmented generation (RAG) pipelines would be advantageous
Experience finding and productionising recent AI models via Hugging Face Transformers or OpenAI APIs would be advantageous
Experience building agentic systems via LangChain, AutoGen, or PydanticAI would be advantageous
Evidence of participating in Open-Source Software development, public hackathons, or other sharable coding samples would be an advantage
Deep expertise in embedding-based architectures, including bi-encoders and cross-encoders, for long-horizon text or temporal prediction tasks would be an advantage
Practical experience building and serving production-ready asynchronous APIs for embedding or other compute-intensive services would be an advantage
Proficiency in Python for high-performance data and model pipelines, with software engineering discipline including testing, versioning, and CI/CD
Good familiarity with the Azure ecosystem, including Azure Kubernetes Service, Azure Batch, Azure AI Foundry, Azure Machine Learning, Azure Blob Storage, and Azure Key Vault, would be an advantage

Benefits

Comp & perks

Competitive salary reviewed annually
Work for a passionate, mission-driven company solving society’s big problems
Work flexible hours around life commitments with a focus on delivering company value rather than hours worked
Training and development opportunities
25 days annual leave (plus bank holidays)
Company pension
Private medical insurance
Generous enhanced parental leave policies
Cycle to work scheme
Flu Vaccinations
Eye Test and contribution towards Glasses for VDU use
Employee Assistance Programme
Mental health and wellbeing support
Remote GP access
Counselling/therapy
Physiotherapy
Medical second opinions