Member of Technical Staff Applied Research

You will develop and train vision-language models for document processing, build data pipelines for curation and synthetic data, and evaluate or fine-tune models against performance targets. You will improve production accuracy, latency, and cost, create benchmarks, and move successful prototypes into production.

Responsibilities

• Develop and train vision-language models for document processing and understanding
• Build data pipelines for curation, synthetic data generation, labeling, and benchmark creation
• Evaluate base models and perform post-training or fine-tuning
• Improve model accuracy, latency, and cost-effectiveness
• Design and maintain benchmarks for extraction, layout, OCR, reasoning, and system reliability
• Work with real-world documents including PDFs, scanned documents, tables, charts, and forms
• Move successful research prototypes into production
• Translate customer requirements into benchmarks, experiments, and model improvements
• Research vision-language models, document AI, post-training, synthetic data, and agentic systems
• Use modern AI coding workflows and tools

Requirements

• Machine learning engineering
• Applied research
• Research engineering
• Model benchmarking
• Model training
• Python
• PyTorch
• Computer vision
• Vision-language model
• NLP
• Document AI
• OCR
• Information extraction
• Agentic AI
• Experimentation
• Production code
• Technical writing
• Synthetic data generation
• Post-training
• Fine-tuning
• vLLM
• Pydantic
• uv
• ruff
• mypy
• Claude Code
• Cursor