Member of Technical Staff - ML Research Engineer, Data

Liquid AI
San Francisco, United States, Boston, Cambridge
Workplace: RemoteFull timeFunction: Research & Scientific (R&D)Education: mastersSkills: ["Problem-solving","Collaboration","Ownership","Communication","Fast learner"]

ML-focused data engineer role within a research-driven team, building and evaluating data pipelines for pre-training, post-training, RL and multimodal tasks. You will filter, synthesize, and generate high-quality data at scale, design synthetic data systems with LLMs, and run ablations to measure impact on model performance, collaborating across pre-training, vision, and audio domains.

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FursaFursa
Liquid AI
Liquid AI
1 year ago

Member of Technical Staff - ML Research Engineer, Data

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 8 hours agoStatus: Live

Job Summary

ML-focused data engineer role within a research-driven team, building and evaluating data pipelines for pre-training, post-training, RL and multimodal tasks. You will filter, synthesize, and generate high-quality data at scale, design synthetic data systems with LLMs, and run ablations to measure impact on model performance, collaborating across pre-training, vision, and audio domains.
Location: San Francisco, United States, Boston, Cambridge
Workplace: Remote
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Build and maintain data processing, filtering, and selection pipelines at scale
  • •Create pipelines for pretraining, midtraining, SFT, and preference optimization datasets
  • •Design synthetic data generation systems using LLMs, structured prompting, and domain-specific generators
  • •Design and run evaluations and ablations to measure dataset's impact on model performance
  • •Monitor public datasets across text, vision, and audio domains

Pay and Benefits

Perks:Health InsuranceVision401k

Key Requirements

  • •Strong Python skills with the ability to quickly comprehend problems and translate them into clean, working code
  • •Solid ML fundamentals: experience training, evaluating, and iterating on models (PyTorch preferred)
  • •Track record of learning new technical domains quickly
  • •3+ years relevant experience with an M.S., or 1+ year with a Ph.D. (5+ years with a B.S.)
  • •Experience with synthetic data generation, data curation, or ML evaluation (nice-to-have)
Experience:Artificial intelligenceMachine learningMultimodal
Education:Master's
Skills:Problem-solvingCollaborationOwnershipCommunicationFast learner
Tech Stack:PythonPyTorchLLMsVLMsComputer visionAudio data pipelinesStructured prompting

Company Brief

Liquid AI
Builds AI infrastructure and tooling to enable real-time, distributed machine learning and orchestration across edge and cloud environments, simplifying deployment and management of intelligent applications.
Industry: AI & Machine Learning
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