Researcher - Pretraining Data Team
London, England, GB
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign and curate high-quality datasets for training and evaluating AI models
Run data ablation experiments to measure the impact of new datasets
Develop and maintain scalable pipelines for ingestion, filtering and annotation
Analyze real-world datasets for quality, diversity and relevance
Build lightweight tools for dataset auditing, visualization and versioning
From the employer’s posting
Design and curate high-quality datasets to power frontier AI models
run experiments on new datasets (data ablations) to assess their impact and determine the most effective data
Develop and maintain scalable data pipelines for ingestion, processing, filtering, and annotation
Analyze real-world datasets to assess quality, diversity, relevance, and identify areas for improvement
Build lightweight tools and workflows for dataset auditing, visualization, and versioning
Tools in this posting
- Python
- Spark
- NumPy
- pandas
Source — Tool mentions in context
Design and curate high-quality datasets to power frontier AI models. Develop novel data collection strategies. Improve dataset quality and integrity. Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data. Develop and maintain scalable data pipelines for ingestion, processing, filtering, and annotation. Analyze real-world datasets to assess quality, diversity, relevance, and identify areas for improvement. Build lightweight tools and workflows for dataset auditing, visualization, and versioning. Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices. Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 10+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR Master's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 8+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience. 2+ years of experience in data analysis or data engineering, including work with large-scale datasets that are unstructured or semi-structured. Proficiency in statistics and exploratory data analysis methods. Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam. Ability to communicate technical findings clearly to research and product teams.
Posting record
Report an errorActively hiringFirst seen by us 9 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 20, 2026 · 9 days ago
- Recorded sightings
- 65
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Design and curate high-quality datasets to power frontier AI models. Develop novel data collection strategies. Improve dataset quality and integrity. Create high-quality datasets for training and evaluation; run experiments on new datasets (data ablations) to assess their impact and determine the most effective data. Develop and maintain scalable data pipelines for ingestion, processing, filtering, and annotation. Analyze real-world datasets to assess quality, diversity, relevance, and identify areas for improvement. Build lightweight tools and workflows for dataset auditing, visualization, and versioning. Collaborate with Safety, Ethics, and Governance teams to ensure datasets meet standards for quality, privacy, and responsible AI practices. Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) Bachelor's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 10+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR Master's Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 8+ years technical engineering experience with coding in languages including, but not limited to, Python and common data libraries (Pandas, NumPy, etc.) OR equivalent experience. 2+ years of experience in data analysis or data engineering, including work with large-scale datasets that are unstructured or semi-structured. Proficiency in statistics and exploratory data analysis methods. Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam. Ability to communicate technical findings clearly to research and product teams.
Source details
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- Location & working pattern
London, England, GB
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