Member of the Technical Staff - Machine Learning
San Francisco$350k - $400k + equityFull-timePosted 4mo ago
About the role
Machine Learning Engineer role focused on applied ML problems in housing verification, underwriting, fraud detection, and document understanding at Two Dots. Not a research role; emphasis on end-to-end model development, deployment, evaluation, and system improvements for fraud and underwriting in real estate domain.
Responsibilities
- Document forensics and detecting fraudulent or edited PDFs
- Cash flow underwriting: inferring a latent financial profile from paystubs, bank statements, business data, or other payment data
- Extracting information from unstructured or noisy sources with very high reliability
- Solving chatbot and agent quality problems that are too hard for others to solve
- Developing models, evaluation systems, and quality management processes from scratch
- Creating broad-based, systemic improvements in ML, LLM, and agent performance
- Educating the team on how to evaluate ML pipelines and workflows, including workflows that involve prompting foundation models
Qualifications
- 3+ years experience
- Strong command of: TensorFlow/PyTorch, training loops, and model deployment
- Metrics-driven evaluation and rigorous quality management
- Statistics, regularization, overfitting, training schedules, and GPU memory management
- Computer vision, NLP, and multimodal understanding problems
- Data warehouse-oriented SQL, especially BigQuery
- Explore-vs-exploit tradeoffs in applied ML work
- Math literate with comfort in ML foundations
Skills
Required:PyTorchDeep LearningNatural Language ProcessingBigQuery
Nice to have:Computer VisionLLMs
Last updated Oct 14, 2026. Interested? Apply on the company site.
About Two Dots
AI fraud prevention and underwriting agent
We're building an AI consumer underwriting automation service.
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