Senior AI Engineer

About the job

Please find the detailed requirement below: 🔹 Key Requirement Overview: · The platform must be completely self-hosted · No OpenAI or third-party AI API usage allowed · No recurring SaaS/API costs for core functionalities · Developers must build and deploy AI capabilities in-house 🔹 Required Skill Set: 1. AI/ML & LLM Expertise: o Strong experience with open-source LLMs (LLaMA, Mistral, Falcon, etc.) o Experience in model fine-tuning (LoRA/QLoRA) o Hands-on with Hugging Face Transformers 2. Model Deployment & Serving: o Experience with model serving tools like vLLM, Ollama, or TGIo Strong knowledge of GPU-based deployments (CUDA) o Experience with Docker/containerized deployments 3. Backend Development: o Strong Python expertise o Hands-on experience with FastAPI and/or Django o Experience in building scalable APIs and microservices 4. NLP & Moderation (Self-hosted): o Experience in building NLP classifiers (toxicity, sentiment, spam detection) o Familiarity with BERT/DistilBERT or similar models 5. Vector Databases & RAG: o Experience with FAISS, ChromaDB, or similar vector databases o Understanding of embeddings and Retrieval-Augmented Generation (RAG) 6. Social Media API Integration: o Direct integration experience with APIs like Facebook, Instagram, LinkedIn, Twitter, YouTube o OAuth, rate limiting, and API handling (no third-party aggregators like Ayrshare) 7. DevOps & Self-Hosting: o Experience with Linux servers, Nginx o Cloud platforms (AWS/GCP/Azure VM-based deployment) o CI/CD pipelines and deployment handling 🔹 Experience Required: · 5–7 years (Mid-level) · 7–10 years (Senior-level) 🔹 Important Note: • Candidates must have practical experience in self-hosted AI systems. Profiles primarily dependent on OpenAI or other external APIs should not be considered.