AI/ML Engineer

Job Description

Role Overview We are looking for an AI/ML Engineer with 3 to 5 years of experience in designing, developing, and deploying AI-powered applications. The ideal candidate should have strong hands-on experience in LLMs, prompt engineering, reasoning workflows (e.g., Chain-of-Thought), and agentic AI frameworks alongside a solid foundation in machine learning. Key Responsibilities Fine-tune reasoning-based LLMs using Chain-of-Thought datasets and techniques. Utilize multiple LLMs (ChatGPT, Claude, Gemini, etc.) and understand their strengths and limitations. Optimize LLM interactions through advanced prompt engineering, few-shot CoT, and iterative refinement. Leverage Retrieval-Augmented Generation (RAG) to combine external context with LLM reasoning. Use platforms like Hugging Face/GitHub to manage, fine-tune, and deploy pretrained models. Implement agentic AI workflows (LangGraph, CrewAI, or custom orchestration systems). Develop scalable backend architectures using FastAPI, Uvicorn, Celery, and async pipelines. Build intelligent automation pipelines involving scraping, entity extraction, and enrichment. Apply best practices in LLM engineering, including: Model training workflows (train/val/test splits, dataset curation) Fine-tuning and instruction-tuning with open-source models Reasoning task evaluation (factuality, coherence, step accuracy) Stay on the cutting edge of AI advancements, from open-weight LLMs to novel prompting strategies. Required Skills & Expertise Excellent communication skills — ability to articulate AI concepts clearly. Hands-on experience in: Prompt engineering for LLM-based applications Agentic AI frameworks (LangGraph, CrewAI, or custom-built) Chain-of-Thought reasoning, few-shot learning, and task decomposition Retrieval-Augmented Generation (RAG) pipelines Web scraping tools (Playwright, Octoparse, BeautifulSoup) System architecture (FastAPI, Uvicorn, Celery, async queues) AI/ML platforms (Hugging Face, Transformers, GitHub-based models) ML Frameworks: PyTorch (preferred), TensorFlow, or Keras Core fundamentals: Data structures, statistics, linear algebra, and optimization Bonus: Familiarity with reasoning datasets (GSM8K, HotpotQA, OpenBookQA) Experience with evaluation metrics for generative models (BLEU, ROUGE, EM, custom validators) Comfortable working across APIs, scraping flows, and backend systems Required Background 3 to 5 years of work experience in AI/ML, backend engineering, or NLP-heavy roles A portfolio of real-world projects — shipped products, agents, scrapers, or research tools Why Join Us? Be part of a stealth-stage, AI-first company solving real-world problems Build reasoning-aware systems powered by LLMs and automation Work at the intersection of trend intelligence, agents, and research Ship fast, own what you build, and have a voice in product direction Competitive salary If you’re passionate about building smart systems that think , we’d love to connect.