Take ownership of data quality and model validation across a live ML platform. Conduct adversarial testing and pipeline validation. Ensure model outputs are explainable, auditable, and aligned with governance and privacy standards.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
ML Data/Ops Engineer (Quality & Validation Focus) – up to £700 p/d – Outside IR35 – Fully Remote – 6–8 weeks with room for extension – ASAP start
Tech: Python, AWS
Most ML contracts are about building models. This one is about stress-testing them before a major release.
I’m looking for an ML Data/Ops Engineer to take ownership of data quality and model validation across a live ML platform.
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You’ll be hands-on with adversarial testing - pushing models with edge cases, bad inputs and failure scenarios to see where they break - alongside pipeline validation and putting proper data quarantine in place in production.
A big part of this is at the ingestion layer - spotting bad or risky data early and stopping it before it even hits downstream pipelines.
Not just fixing issues late, but preventing them from entering the system in the first place.
You’ll also be making sure model outputs are explainable, auditable, and aligned with governance and privacy standards.
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If you’ve worked on ML systems in production and know where things usually go wrong, then this is the contract role for you.
Experience in a regulated environment (fintech, healthcare, banking, gambling etc.) would be a big plus.
Money is cracking up to £700 p/d, outside IR35, fully remote.
Please apply or message me! No CV needed right now. Feel free to apply using your LinkedIn profile, we can cross the CV bridge later.
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