> Markdown version of [/jobs/ext/4628319-senior-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/4628319-senior-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). --- # Senior Machine Learning Engineer - **Company:** True Talent Solutions LLC - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $200,000 - $325,000 - **Contract:** Permanent contract - **Skills:** Computer Vision, Information Extraction, Python (Programming Language), Machine Learning, Language Modeling, Software Deployment, Unstructured Data, Large Language Models, Information Technology, Build Tools, Machine Learning Operations, Streamlit Framework, Data Pipelines - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25304_f08067dafbb7927c22aaa5ec32990faf ## About the Role * At least 4 years of full-time machine learning engineering experience after graduation, including training, fine-tuning, and evaluating models used in production. * Hands-on experience with OCR and document understanding, plus one or more of vision-language models, computer vision, or large language models. * Strong computer science or engineering fundamentals and experience shipping models to users. * Proficiency with Python and experience with relevant tools such as Streamlit. * Startup experience is valued. A first- or second-author paper in computer vision, vision-language models, or document understanding is a plus. ## Description Join a machine learning team building models that interpret complex documents and turn unstructured information into useful inputs for language models. You will own work end to end, from research and experimentation through production deployment, helping improve document understanding for enterprise workloads., * Train and deploy models for parsing and interpreting unstructured data. * Experiment with techniques to improve language model accuracy and build tools to measure their impact. * Develop data pipelines, evaluate model performance, and integrate models into the product. * Work directly with company leadership and customers to shape product direction and engineering strategy.