Hugging Face Proxy Job Support — Transformers, Fine-Tuning, RAG, Agents & LLM Serving

It is real-time, hands-on help from experienced LLM engineers during your working hours — on your actual project. We help with Transformers training and inference, PEFT/LoRA/QLoRA fine-tuning, TRL post-training, Sentence Transformers and RAG, Diffusers, agents (smolagents), and deployment on Inference Endpoints, vLLM or TGI, plus the huggingface_hub, hf CLI, tokens, gated models, and GPU work around them. It is delivered live, confidentially, and same-day where needed, anywhere in the world.

Transformers (AutoModel/AutoTokenizer, pipeline, Trainer, generate, device_map, tensor parallelism, attention and quantization backends), PEFT (LoRA, QLoRA, adapters, merging), TRL v1 (SFTTrainer, DPOTrainer, GRPOTrainer, RewardTrainer, DistillationTrainer), Accelerate, Sentence Transformers (bi-encoders, cross-encoder rerankers, sparse and multi-vector/ColBERT), Diffusers, Datasets, Tokenizers, Safetensors, Optimum (including Optimum-Neuron for Trainium/Inferentia), bitsandbytes, the Kernels / Kernel Hub, huggingface_hub and the hf CLI (with Xet storage), Inference Endpoints, Inference Providers, TGI, TEI, vLLM, Gradio and Spaces, Trackio, Lighteval, Argilla/Distilabel, and AutoTrain.

Yes. We provide dedicated production support — CUDA out-of-memory during training and inference, tokenizer/model config mismatches, LoRA adapter loading/merging failures, quantization dtype errors, gated-model 401/403 and token-scope problems, Inference Endpoint cold starts and autoscaling, slow tokens/sec and high time-to-first-token, RAG retrieval collapse, and embedding-dimension mismatches — with an engineer on the call. See our Hugging Face production support page.

Yes. We offer Hugging Face and LLM interview support and get-interview-scheduled services for LLM Engineer, Generative AI Engineer, NLP Engineer, ML Engineer, RAG Engineer, and Applied AI roles — live guidance during interviews, real-time interview support, and profile positioning so the calls come in the first place. Hiring decisions are always made solely by employers.

Yes. This cluster reflects the ecosystem state through September 2026 — Transformers v5 as the model-definition framework, TGI moving to maintenance mode with HF recommending vLLM/SGLang for new serving, the CLI rename to hf, Xet storage replacing Git LFS, Inference Providers replacing the old serverless Inference API, TRL v1 with stable GRPO and DistillationTrainer, Sentence Transformers v5+ with four model types, and newer projects like Trackio and OpenEnv (experimental). We verify version-sensitive details before advising.

Message us on WhatsApp with your Hugging Face stack, your situation (job support, production issue, interview, or profile), and your timeline. We match you with the right LLM engineer — usually the same day. Every engagement is confidential and NDAs are available on request.