Remote positions
Browse vetted remote PyTorch positions at companies building with deep learning, LLM fine-tuning, and production model serving — all roles manually reviewed.
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Full-time roles and fixed-scope freelance missions — matched to your AI skills.
Posted 8 months ago
We operate drone delivery for medical supplies in rural Ghana and Kenya. Our fleet of 15 drones makes 80+ deliveries per day. Currently routes are pla...
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Posted 8 months ago
We build AI-assisted diagnostic tools for radiologists. Our current product analyses chest X-rays for abnormality detection. We're now expanding to CT...
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Posted 8 months ago
We're a mid-size mobile game studio. Our game is an open-world RPG where we want procedurally generated quests and dungeons that feel authored — not o...
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Posted 8 months ago
We make vibration, acoustic, and thermal sensors for industrial environments. Inference currently goes to cloud. We want it on the sensor. Need someo...
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Posted 9 months ago
Consumer goods company. 4 brands. We monitor Twitter, Instagram, TikTok comments and Google reviews — currently manually, by two people who read throu...
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Role guide
PyTorch has become the default framework for deep learning research and production at leading AI labs. Remote PyTorch jobs range from model training and fine-tuning to deployment and inference optimisation. The most competitive candidates combine strong PyTorch internals knowledge with production ML system experience.
What remote PyTorch jobs are posted on RemoteAI?
Primarily deep learning engineering roles, LLM fine-tuning positions, and research engineering jobs. Most require hands-on PyTorch model development experience — not just API-level usage.
Do I need Hugging Face experience for PyTorch jobs?
Most companies posting PyTorch roles on RemoteAI use Hugging Face Transformers. Strong familiarity with the HF ecosystem — especially for fine-tuning and inference — significantly improves your application.
What seniority levels are available for remote PyTorch jobs?
Mostly mid-to-senior. PyTorch roles tend to require production experience — companies building LLM or vision systems want engineers who have debugged training instability, not just run tutorials.
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