Contract Assignment: Data Engineer – AI Research & Dataset Integrity (London Hybrid) Reference: BH 7210 Hourly Rate: Competitive – DOE – 40 hrs/week Contract Type: Inside IR35 Duration: 12 months (with potential extension) Start Date: ASAP Location: London (3 days/week onsite at Kings Cross office) Must be able to contract via PAYE This role does not provide sponsorship – candidates must have existing right to work in the UK and be UK-based. Responsibilities: • Design, build, and maintain scalable data pipelines to support advanced AI research initiatives involving large-scale text, image, and video datasets. • Collaborate closely with cross-functional teams including software engineers and researchers to prepare datasets for use in intelligent automation systems. • Handle data onboarding, preprocessing, filtering, post-processing, and reintegration using internal tools and Python. • Ensure datasets meet quality and compliance standards by implementing data risk mitigation strategies. • Contribute to the automation of data handling processes within AI infrastructure. • Operate within a collaborative and research-focused engineering environment. Requirements: • 2–4 years of professional experience in data engineering or software engineering roles. • Proficiency in Python and building/maintaining production-grade data pipelines. • Strong skills in data cleaning, transformation, filtering, and validation. • Experience working with text, image, or video datasets at scale. • Excellent collaboration and communication skills. • Willingness and ability to work onsite in London 3 days per week (hybrid model). Preferred Background: • Exposure to machine learning or AI research environments. • Familiarity with tools such as PyTorch and large-scale data filtering pipelines. • Prior experience in content moderation, dataset integrity, or risk mitigation workflows. • Background in fast-paced, research-driven, or high-growth tech environments. Required Qualification(s): • Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field (or equivalent experience)