Machine Learning Engineer

In Technology Group • Full-time • Oxford, GB • £50k - £80k / year • 1d ago

Job Title: Machine Learning Engineer

Location: Oxford, UK (Hybrid – 2 days a week in office)

Salary: £50,000–£80,000 + bonus

About Us

We’ve partnered with an award-winning software company based in Oxford, building AI-powered platforms that help organisations extract insights, automate workflows, and drive smarter decisions across industries — from logistics and legal tech to research and government.

Backed by leading UK tech investors and home to a team of engineers, product thinkers, and data scientists, we’ve scaled rapidly in the last 3 years and are now looking for a Machine Learning Engineer to help us push our platform to the next level.

You’ll join a collaborative, pragmatic team that values clean code, creative problem-solving, and real-world impact. If you're excited by applied ML and building things that get used — this is for you.

What You'll Do Daty to Day

Develop, train, and deploy ML models in production for a range of use cases: document understanding, intelligent search, prediction engines, and recommendation systems
Collaborate with product managers, software engineers, and customers to scope and define ML features
Build scalable and reusable model pipelines and deploy using best-in-class MLOps practices
Monitor, tune, and maintain models post-deployment with attention to performance, drift, and explainability
Apply techniques like NLP (LLMs, transformers, embeddings), supervised/unsupervised learning, semi-structured data parsing, and anomaly detection
Participate in sprint planning, code reviews, and architecture discussions — we’re a flat, fast-moving team

What You’ll Bring to the team

Strong Python skills and experience with ML frameworks like scikit-learn, TensorFlow, PyTorch, Hugging Face
Solid grasp of data wrangling, feature engineering, and model evaluation techniques
Proficiency in designing and deploying production-ready ML pipelines
Familiarity with cloud platforms (AWS/GCP/Azure) and tools like Docker, Airflow, MLflow, or Kubeflow
Understanding of core ML algorithms and when to apply them: classification, clustering, regression, etc.
Comfort with SQL and working in a software engineering environment (e.g., version control, CI/CD)
Great communication skills — you can explain your ideas to technical and non-technical people alike

Nice to Have (but Not Deal-Breakers):

Experience working with text-heavy datasets, OCR, or document intelligence
Familiarity with vector search, semantic similarity, or RAG (Retrieval-Augmented Generation)
Interest in Human-in-the-Loop ML, active learning, or explainable AI
Prior startup or scale-up experience, ideally in B2B SaaS or platform-based ML
Familiarity with TypeScript/JavaScript or APIs if you've worked closely with full-stack teams

What’s In It for You