Senior Machine Learning Engineer

Botminds does advanced document understanding: the platform reads financial statements, contracts, and operational paperwork, and turns them into decisions people can trust. The models behind that reading are this role’s job — building them, tuning them, and running the infrastructure that keeps them honest in production.

You will work at the seam between research and engineering, close to the platform team, turning what works in a paper into what works for a credit analyst at 9am.

What you’ll do

You will design, build, and deploy machine learning models with a focus on large language models and deep learning, then fine-tune them for accuracy, latency, memory, and throughput — production numbers, not benchmark numbers. You build and manage the MLOps infrastructure for experimentation, A/B testing, and deployment, and you own LLM pipelines built on frameworks like LangChain and LlamaIndex. Alongside that, you work with cross-functional teams to shape AI solutions for concrete business problems, writing solid Python throughout.

What you bring

2–5 years of AI/ML experience in the software industry, with real problem-solving depth.
Solid grounding in machine learning, deep learning, and large language models.
Expert Python.
Familiarity with LLMs such as Llama, Zephyr, Mistral, and the OpenAI APIs, plus transformer models like BERT, GPT, and RoBERTa.
Working knowledge of ML frameworks (PyTorch, LangChain, spaCy) and experience building MLOps infrastructure.

Why this role

Document understanding is the product here. Your models get exercised against tens of thousands of real enterprise documents, and the feedback loop from user to model is short. If you want to move your career deeper into ML with strong people around you, this is a place to do it by shipping, not shadowing. Full time, Engineering department, based in Chennai.