Machine Learning Engineer We're on a mission to redefine how organizations process and extract value from unstructured documents-think complex PDFs, financial statements, or medical records. Our platform is already trusted by leading tech companies, and now we're scaling our ML team to power the next generation of document intelligence.
We're looking for a
Machine Learning Engineer who is passionate about deploying large-scale, production-grade AI systems that work on real-world, noisy data. If you're excited about fine-tuning LLMs, building high-accuracy pipelines, and solving deep technical challenges with a hands-on team, this is for you.
What You'll Do- Build and deploy machine learning models for understanding and extracting information from complex, unstructured documents (PDFs, spreadsheets, scanned images, etc.)
- Fine-tune and evaluate Large Language Models (LLMs) using domain-specific data
- Develop Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, and Vector DBs
- Build data pipelines, labeling workflows, and evaluation metrics to continuously improve model performance
- Rapidly prototype tools and internal apps (e.g. Streamlit dashboards) for dataset exploration and hypothesis testing
- Work closely with product, infra, and customer teams to ship features and iterate on feedback
- Drive innovation by staying up to date with the latest research in NLP, LLMs, and document AI
What We're Looking For- 3-7 years of industry experience in machine learning, with at least 2 years focused on production ML systems
- Strong Python skills, with deep experience in ML frameworks such as PyTorch, HuggingFace, or TensorFlow
- Practical experience with LLMs, NLP techniques, and tools like LangChain, RAG, sentence transformers, etc.
- Familiarity with model evaluation methods (BLEU, ROUGE, retrieval precision, etc.)
- Experience deploying models on cloud infrastructure (AWS Sagemaker, Bedrock, EKS, or similar)
- Proficiency with MLOps, containerization (Docker, Kubernetes), and API development (FastAPI)
- Ability to work independently in a fast-paced, collaborative startup environment
Bonus Points- Experience in document parsing, OCR, or vision-language models
- Familiarity with streamlining CI/CD for ML pipelines
- Startup experience or having shipped products end-to-end
- Interest in GenAI and multi-agent LLM workflows