1 month ago

AI Researcher

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Build embodied AI by advancing world-model research for robots, spanning model and data, data infrastructure, ML infrastructure, and evaluations. Design and operate large-scale training and inference systems to keep GPUs efficiently utilized, create data pipelines for multimodal and on-policy robot experience, and develop evaluation tooling that links pre-training metrics to real-world performance. Ship research into deployed robot capabilities and help accelerate the lab’s learning flywheel.

Location: United States

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Build large multi-modal generative world models that learn from robot experience, including model architecture, tokenization, and large-scale training/data processing.
•Design and operate data infrastructure for training on visual and robot data, including web-scale media and on-policy robot experience with scalable annotation/curation.
•Own distributed training and inference systems to keep GPUs utilized, improving training throughput and inference speed.
•Create evaluation infrastructure that connects pre-training metrics to real-world robot performance via benchmarks, eval frameworks, model ranking, and iteration tooling.
•Ship research to production by owning the path from experimental results to deployed robot capabilities and measuring impact in real environments.

Pay and Benefits

Salary: USD 250,000 - 350,000 annually

Perks:Health InsuranceDentalVision401kPaid Leave

Key Requirements

•Strong Python and PyTorch (or an equivalent deep learning framework) with experience in large-scale codebases and data tooling/visualization.
•Experience in at least one of the four AI pillars: model and data, data infrastructure, ML infrastructure, or evaluation protocols.
•Degree in Computer Science, Machine Learning, or a related field; graduate-level education or equivalent research experience preferred.
•Track record of impact via published research, deployed production in modern AI systems, or infrastructure that measurably accelerates teams.
•Demonstrated depth plus engineering rigor to push work from promising training into deployed capabilities.

Education:

Skills:Research depthEngineering rigorScale-first mindsetHigh-agency contributionBottleneck identification

Tech Stack:PythonPyTorchTorchTitanDeepSpeedFSDP/ZeROCUDATritonTensorRTETLQuantizationPTQQATINT8FP8Multi-modal generative modelsWorld modelsDiffusion modelsAutoregressive architectures

Company Brief

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