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DNA325

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5 jobs
DNA325
32 views 2 months ago

Applied AI Engineer

Open 46d Remote

Applied AI Engineer at an AI-native, remote-first product startup reimagining email, notes, and task tools. Day to day: own AI features end-to-end — prompt, tool, memory, and agent design, model fine-tuning and serving — turning model output into reliable product behavior using Python, PyTorch/JAX, vLLM, and vector DBs.

AI API Data Pipelines Fine Tuning JAX +7 skills
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DNA325
29 views 2 months ago

Applied AI Engineer (ES, PT)

Open 46d RemoteEurope

An Applied AI Engineer joins a remote-first, AI-native startup (client of DNA325) building AI-native replacements for email, notes, and task tools. The engineer ships AI features end-to-end — prompts, agents, memory, inference infra — using Python, PyTorch/JAX, LLM APIs, vLLM, and vector databases.

AI API Data Pipelines Fine Tuning JAX +7 skills
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DNA325
20 views 2 months ago

Member of Technical Staff, Machine Learning

Open 46d RemoteEurope
Spain
Madrid

Join an AI-native productivity company's small team to build core ML components across data, training, evaluation, and inference — fine-tuning models, building data pipelines, and debugging real production ML systems using Python, PyTorch/JAX, and GPUs, while shipping iteratively under latency, cost, and reliability constraints.

AI Data Pipelines Fine Tuning JAX Machine Learning +2 skills
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DNA325
19 views 2 months ago

Member of Technical Staff, Machine Learning (remote, Spain)

Open 46d RemoteEurope
Spain
Madrid

Machine learning engineer building core ML components — data pipelines, training, evaluation, and inference — for an AI-native productivity product (reimagined email/notes/tasks), shipping and debugging real production ML on GPUs. Core stack: Python, PyTorch/JAX.

AI Data Pipelines Fine Tuning JAX Machine Learning +2 skills
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DNA325
16 views 2 months ago

Principal Machine Learning Engineer

Open 46d RemotePrincipal

Principal Machine Learning Engineer turning research direction into production-grade ML systems for an AI-native productivity startup: building end-to-end training, evaluation, and inference pipelines, fine-tuning large models, and optimizing GPU deployment. Core stack spans PyTorch/JAX, distributed training frameworks (DeepSpeed, FSDP, Ray), and LLM inference tooling.

AI Deep Learning DeepSpeed Distributed Training Fine Tuning +10 skills
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