Junior AI-ML Engineer

Job Description

Your mission in the first 12 months Fine-tune & play – take open-weight models (e.g. Mistral-7B-Instruct) and run LoRA or QLoRA experiments; report wins and trade-offs. Build data pipes – write small Python scripts that convert ERP tables, log streams, or image folders into tidy CSV / Parquet for training. Prototype RAG – load a batch of PDFs into a FAISS index, craft a prompt, and demo a chatbot that cites its sources. Model hygiene – add unit tests for prompt functions, set up basic latency / quality dashboards, hook OpenAI or Bedrock usage into CloudWatch. Team enablement – improve README files, jot quick snippets (“How to quantise with bits-and-bytes”), record Loom videos as you learn. What we’re looking for 0–2 yrs industry or strong capstone / internship in ML, NLP, or CV. Comfortable Python (Pandas, NumPy, basic PyTorch or TensorFlow). Some exposure to HuggingFace Transformers or OpenAI / Bedrock SDK. Knows how to use Git branches, open PRs, and write clear commit messages. Loves reading research blogs / papers and trying things fast. Bonus points if you have: a Kaggle medal, a Discord bot, or a small open-source repo that loads an LLM. Why you’ll like it here Real models in prod – your code will power WhatsApp workflows and dashboard narratives, not sit in a sandbox. Mentorship – pair weekly with a senior MCP Architect; monthly office hours with our Data-Science advisor. Tool budget – GPU credits, books, or a course of your choice each quarter. Hybrid freedom – work fully remote or drop into our Hyderabad office any time for whiteboard jams. How to apply Share a résumé and link to one small ML project (GitHub, Colab, Kaggle). Write 100 words on the coolest bug you solved while training or deploying a model. Short-listed candidates complete a two-hour take-home: fine-tune a tiny model or build a RAG proof-of-concept and explain your choices. Fresh minds + real models = fast progress. If you’re eager to learn and ship, let’s talk. Show more Show less