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Remote Research Engineer jobs

27 open positions in the United States, newest first.

Research engineers build the software and run the experiments that turn research ideas into working results, most often in machine learning. They sit between research scientists and production engineers, and are responsible for training infrastructure, evaluation code and reproducible experiments as well as contributing ideas of their own.

About the Research Engineer role

What the work looks like

  • Implement model architectures and training loops from papers or internal proposals in PyTorch or JAX.
  • Run and monitor large training jobs on GPU clusters and debug failures in distributed runs.
  • Build evaluation harnesses and benchmarks that measure whether a change actually improved the model.
  • Profile and optimize data loading, training and inference code for speed and memory use.
  • Write up experiment results with plots and ablations and present them to the research group.

What employers ask for

  • Strong Python and software engineering practice
  • Deep learning frameworks such as PyTorch or JAX
  • Distributed training and GPU computing
  • Linear algebra, probability and machine learning fundamentals
  • Experiment tracking and reproducible research workflows
  • Reading and implementing research papers

Doing this job remotely

Experiments run on remote compute clusters, so the work itself does not depend on location. What is harder remotely is the informal discussion that shapes research direction, and some labs prefer researchers on site for that reason. Remote roles rely on written experiment logs, shared notebooks and regular research meetings across time zones.

Where it comes from and where it leads

Typical backgrounds are software engineering with a machine learning focus, or a master's or doctorate in a quantitative field. The role leads to senior and staff research engineer, research scientist, or technical leadership of a research or applied machine learning team.