ML Engineer

About The Job

This role is for one of our client companies — a VC-backed Digital Document Infrastructure startup that has raised $6.5M USD in funding.

Role Overview: ML Engineer (3+ Years Experience)

We are seeking an experienced Machine Learning Engineer to design, deploy, and scale advanced NLP and Computer Vision models. If you excel at turning unstructured document data into production-ready AI solutions, we want to hear from you.

What You'll Do

• Design, develop, and deploy ML models for document intelligence, content processing, and automated information extraction.
• Build end-to-end ML pipelines for processing unstructured text, images, scanned documents, and PDFs.
• Develop and improve NLP and CV solutions for document classification, entity extraction, semantic search, and document understanding.
• Experiment with deep learning architectures, Transformers, and LLM-based approaches to solve real-world document processing challenges.
• Convert research prototypes and experimental models into reliable, scalable, production-ready systems.
• Evaluate model performance using appropriate metrics, statistical analysis, benchmarking, and error analysis.
• Optimize model accuracy, inference speed, scalability, and resource utilization for production workloads.
• Build and maintain REST APIs and integrate ML models into existing product workflows.

You're A Great Fit If You

• Have 3+ years of hands-on experience in Machine Learning Engineering with a strong focus on Computer Vision, NLP, or document intelligence.
• Possess strong proficiency in Python and have experience writing production-quality, maintainable code.
• Have practical experience building, training, evaluating, and deploying machine learning and deep learning models.
• Demonstrate a strong understanding of deep learning architectures (CNNs, Transformers), fundamental ML algorithms, mathematics, and statistics.
• Are experienced with PyTorch and the Hugging Face Transformers ecosystem.
• Have hands-on experience handling unstructured text and document data, including classification, information extraction, semantic search, or document understanding.

Why Join Us?

• Own the deployment of production ML systems that redefine document infrastructure.
• Drive immediate product impact with $6.5M in Series A backing.
• Accelerate your career in a high-growth, remote-first engineering culture.
• Collaborate daily with a world-class, ambitious team of builders.