SR2 | Socially Responsible Recruitment | Certified B Corporation™
commercial teams to bring ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, HuggingFace or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready More ❯
and writing feature/unit tests Ability to refactor legacy applications using modern standards Desirable Skills Experience with React or Vue.js Familiarity with AI tools/APIs (e.g., OpenAI, HuggingFace) Exposure to CI/CD pipelines Experience with Meilisearch and WebSockets More ❯
understand large and fast-moving websites. The company has raised a $1.8m pre-seed from tier-1 seed investors and angels who have backed companies like Figma, Revolut, Notion, HuggingFace, Vercel, and Wise. Fruitful aims to address the challenges of understanding software in a world of infinite software where code is not written by humans. Fruitful's More ❯
to monitoring models in production Strong understanding of neural networks, CNNs, RNNs, LSTMs, and transformers Experience building automated data pipelines Hands-on experience with LLM tooling and libraries (e.g., HuggingFace Transformers/PEFT, tokenisers, spaCy or similar) Experience shipping NLP systems: prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge More ❯
to monitoring models in production Strong understanding of neural networks, CNNs, RNNs, LSTMs, and transformers Experience building automated data pipelines Hands-on experience with LLM tooling and libraries (e.g., HuggingFace Transformers/PEFT, tokenisers, spaCy or similar) Experience shipping NLP systems: prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge More ❯
london (city of london), south east england, united kingdom
Glite Tech
to monitoring models in production Strong understanding of neural networks, CNNs, RNNs, LSTMs, and transformers Experience building automated data pipelines Hands-on experience with LLM tooling and libraries (e.g., HuggingFace Transformers/PEFT, tokenisers, spaCy or similar) Experience shipping NLP systems: prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge More ❯
