Research Engineer in Data

Synthesia
Europe, London
Workplace: HybridFull timeFunction: Research & Scientific (R&D)Skills: ["Collaboration","Communication","Problem-solving"]

Senior, data-focused role joining Synthesia’s Data team to manage data lifecycles for researchers, building a high-quality data lake and scalable pipelines to improve model performance. You’ll collaborate with model training teams on features/annotations from video and audio data, shaping long-term data strategy and infrastructure at the intersection of applied ML and data engineering.

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FursaFursa
Synthesia
Synthesia
7 months ago

Research Engineer in Data

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Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live

Job Summary

Senior, data-focused role joining Synthesia’s Data team to manage data lifecycles for researchers, building a high-quality data lake and scalable pipelines to improve model performance. You’ll collaborate with model training teams on features/annotations from video and audio data, shaping long-term data strategy and infrastructure at the intersection of applied ML and data engineering.
Location: Europe, London
Workplace: Hybrid
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Sr. Manager level

Key Responsibilities

  • •Own the data lifecycle for researchers, from sourcing to large-scale processing and delivery of datasets powering models
  • •Collaborate with model training teams to extract features and annotations that elevate dataset quality and model performance
  • •Contribute to the design, build, and operation of data pipelines and ML infrastructure
  • •Help shape the longer-term data strategy and orientation of the data team
  • •Ensure datasets are well-documented, tested, and maintainable to support scalable research efforts

Pay and Benefits

Perks:EquityAnnual BonusRemote WorkAnnual Leave

Key Requirements

  • •A strong background in data-centric, applied Machine Learning with hands-on experience in improving model performance through data quality, curation, labeling, and evaluation rather than model architecture alone
  • •Experience working on the data layer of Generative AI products, particularly involving images, video, or audio
  • •Excellent Python skills with a focus on writing clean, maintainable, and well-tested code
  • •Hands-on experience designing, building, and operating workflow orchestration systems and large-scale data processing pipelines
  • •Ability to collaborate with model training teams to extract features/annotations and influence data strategy
Experience:AiGenerative aiData engineeringMl infrastructure
Skills:CollaborationCommunicationProblem-solving
Tech Stack:PythonWorkflow orchestrationData pipelinesData lake

Company Brief

Synthesia
Provides an AI video generation platform that creates realistic synthetic presenters and video content from text, enabling enterprises to produce scalable training, marketing, and communications videos without cameras or actors.
Industry: AI & Machine Learning
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series C
Headquarters: London, United Kingdom
Founded: 2017
WebsiteLinkedIn