High Heaton
Misterton
Stoke Bishop
Snaith
Beacon Park
Cross Inn
Gipsyville
Headstone, Greater London
Week
Mockbeggar
North Seaton
Gretna Green
Herne Hill
East Parley
Halkyn, Flintshire
Bearsden
Pembroke
Berkhamsted, Hertfordshire
Studley
Inverkeithing, Fife

Machine Learning Engineer

Link copied!
Location
Job type Temporal
Publication date 10 February 2026
3 people applied for this job

General Description

Machine Learning Engineer (Contract)

Apply now, read the job details by scrolling down Double check you have the necessary skills before sending an application.

Duration: 5 weeks (with potential for extension)

Status: Outside IR35

Location: Remote (UK-based)

Start Date: ASAP

About the Role

We are seeking an experienced Data & ML Contractor to deliver a proof of concept using static, structured datasets. This is a focused, pragmatic engagement centred on data preparation, feature engineering, and anomaly detection – with an emphasis on clear, interpretable outputs for stakeholders.

This is not a heavy Data Engineering or MLOps engagement.There is no requirement for live pipelines, streaming ingestion, or ongoing automated refresh. The successful candidate will work hands-on to profile data, engineer meaningful features, develop detection logic, and communicate findings effectively to non-technical stakeholders.

Essential Skills & Experience

  • Strong Python for data processing and analytics (e.g., pandas, numpy; scikit-learn or equivalent)
  • Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts
  • Feature engineering: ability to craft interpretable, business-relevant features
  • Anomaly detection experience: practical knowledge of rule-based and statistical methods; ML-based approaches where appropriate
  • Requirements & communication: ability to work with xwzovoh stakeholders, define success criteria, and explain outputs clearly

Desirable (Nice to Have)

  • Power BI / BI visualisation (or similar) to support validation and stakeholder-facing outputs
  • Familiarity with Azure for accessing datasets or sharing PoC artefacts (basic storage/compute)
  • Ability to outline what would be needed to scale the PoC toward production later (without implementing full MLOps now)

Apply directly or contact

Verification

Verified company

The company details and address have been verified.