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.
Autoscaling policies for GPU inference clusters are typically reactive: scale up when utilization exceeds a threshold, scale down when it drops below...
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Sports performance broadcasting is moving from descriptive to analytical: viewers want to know not just what happened but what it means in performance...
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Posted 3 months ago
United States — New York (UTC-4)
LLM-based systems increasingly operate with access to tools, APIs, databases, and external services. A customer service bot connected to a CRM can loo...
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LLMs operating on long documents face a specific faithfulness failure mode: the model generates an answer that's plausible and fluent but isn't actual...
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GPU inference throughput is a function of batch size: a GPU executing a batch of 32 inference requests is far more efficient than the same GPU process...
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Knowledge graphs encode what is true. Temporal knowledge graphs encode what was true and when — capturing that an entity's properties change over time...
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We're building an AI-native underwriting platform for specialty insurance lines. Our clients have already told us that premium leakage — the gap betwe...
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Posted 3 months ago
United States — Los Angeles (UTC-7)
Have you ever debugged a distributed training job that failed at step 47,832 of 50,000 and lost 40 hours of gradient accumulation? We build the infras...
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Pydantic, LangChain structured output, and JSON Schema are the tools we live in. If you've spent time making LLMs reliably produce machine-parseable o...
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Our climate tech team works async across 6 continents, and we believe the best energy modelers aren't necessarily in the same city as our servers. If...
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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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