# Machine Learning Engineer at Xantura

> Hybrid · United Kingdom · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/pinpoint%3Axantura%3A565121 (read 2026-11-08).

## Facts (observed)

- Company: [Xantura](https://alderhq.app/companies/xantura)
- Location text: London, Southwark
- Where it can be done from (inferred): Hybrid · United Kingdom (evidence: "Location: London, Southwark")
- Posted: already open when tracking began; date unknown
- First seen by alder: 2026-11-07 · last verified: 2026-11-08
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://xantura.pinpointhq.com/en/postings/fdfd6308-0a6a-48d7-b780-7e7d83070d85
- Skills listed (inferred): Python, FastAPI, Azure, Kubernetes, Airflow, PyTorch, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (London, n 20): p25 £102k, median £213k, p75 £348k

## Description (the employer's text)

In this role you will work in the Platform team – a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business.

### Responsibilities

- Own and advance a predictive modelling platform that scales across problem types and tenants, using it to design, implement, and iterate models (embedding-based sequence encoders, temporal survival models, gradient-boosted decision trees) that predict key vulnerabilities in housing, health, and other social domains.
- Track developments in ML and frontier models, running structured experiments to bring promising techniques into production safely.
- Build robust evaluation pipelines, training datasets, and model infrastructure to support continuous improvement of natural language & predictive analytics.
- Ensure responsible AI deployment, embedding ethical and regulatory considerations into every stage of development.
### Skills

- 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 (or Airflow, Prefect, etc.).
- Hands-on experience with common ML libraries and frameworks, e.g. PyTorch, scikit-learn, and gradient-boosting libraries such as XGBoost or LightGBM.
- Clear evidence of practical experience defining and deploying containerised systems, i.e.:
- Implementing APIs for internal services, e.g. via FastAPI;
- Deploying containerised systems to production, in particular via Kubernetes.
In addition, the following would be an advantage:

- PhD in Computer Science, Machine Learning, or a related field with a strong publication record in text analytics, representation learning, or applied predictive modelling.
- Practical experience productionising LLMs, i.e.:
- Working with vector databases and developing retrieval-augmented generation (RAG) pipelines – experience setting up/configuring vector DBs, as well as using, would be advantageous;
- Finding and productionising recent AI models (e.g. via Huggingface (transformers), OpenAI APIs);
- Building agentic systems (e.g. via LangChain, AutoGen, PydanticAI).
- Evidence of participating in Open-Source Software (OSS) development, public hackathons, or other sharable coding samples.
- Deep expertise in embedding-based architectures, including bi-encoders, cross-encoders, etc. for long-horizon text or temporal prediction tasks.
- Practical experience building and serving production-ready, asynchronous APIs for embedding and/or other compute-intensive services.
- Proficiency in Python for building high-performance data and model pipelines, with strong software engineering discipline (testing, versioning, CI/CD).
- Good familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Batch, Azure AI Foundry, Azure Machine Learning, Azure Blob Storage, Azure Key Vault) .
This is a Hybrid opportunity with the expectations of being in the office 1 - 2 days a week.

### Benefits

- 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

---
Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/pinpoint%3Axantura%3A565121 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.