> Markdown version of [/jobs/ext/4618754-founding-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/4618754-founding-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Founding Machine Learning Engineer

- **Company:** Recruiting from Scratch
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $150,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automated Storage and Retrieval Systems, Big Data, Computer Clusters, Encodings, Distributed Computing Environment, Information Retrieval, Python (Programming Language), Knowledge-Based Systems, Machine Learning, Pytorch, Large Language Models, Transformer Architectures, Machine Learning Operations, Feature Extraction, Entity Resolution, Model Inference
- **Published:** November 7, 2026
- **Apply:** https://www.careerbuilder.com/job-details/founding-machine-learning-engineer-san-francisco-ca--ace3bac9-8d9d-496f-8754-45d794251e64

## About the Role

Machine Learning, Needs Assessment, Team Lead/Manager, Startup, Artificial Intelligence (AI) Agents, Structured Data, Artificial Intelligence (AI), Application Programming Interface (API), Machine Learning, Power Generation, * 3+ years of experience building and shipping production ML systems, particularly in NLP, information retrieval, or entity resolution

 * Strong hands-on experience with Python and PyTorch
 * Deep understanding of transformer architectures, including training and fine-tuning encoder models
 * Experience building retrieval systems, classifiers, or embedding-based systems
 * Familiarity with representation learning techniques (e.g., contrastive learning, metric learning)
 * Experience applying LLMs to structured data problems (e.g., extraction, classification, generation)
 * Strong problem-solving skills with the ability to work on ambiguous, large-scale data challenges
 * High ownership mindset with a strong bias toward execution in fast-paced environments

Preferred

 * Experience with entity resolution or record linkage at scale
 * Background in multilingual or cross-lingual NLP
 * Experience building taxonomies, ontologies, or knowledge systems
 * Familiarity with distributed training on GPU clusters
 * Experience scaling LLM inference pipelines in production
 * Research publications or open-source contributions in NLP/IR