Senior Machine Learning Engineer - Remote

Overview

Marker Learning is on a mission to help schools and parents access more affordable and accessible learning disability (e.g., dyslexia) assessments. 1 in 5 students has a learning disability such as dyslexia, which makes it harder for them to read, spell, and write--despite their intelligence. While receiving a proper evaluation for a learning disability could be the most impactful event in a student’s life, it is estimated that only 4% of students receive a diagnosis because of the high costs of evaluations and lack of access to qualified psychologists. Undiagnosed students are 3x more likely to drop out of high school, 5x more likely to be unemployed, and tend to experience elevated levels of anxiety and depression. By leveraging proprietary technology developed by leading experts, the end-to-end Marker evaluation is completed in a fraction of the time compared to traditional assessment methods. Marker is a rapidly growing start-up backed by some of the most mission-driven and reputable venture capital firms and education non-profits. Join us in our mission to inspire and support all students on their unique learning paths!

In Short

• Own and scale the end-to-end ML lifecycle: data pipelines, training, serving, monitoring, and evaluation.
• Build and productionize systems for AI document parsing (OCR, classification, extraction).
• Develop LLM-powered summarization and content generation.
• Create chat interfaces for editing special education reports.
• Optimize model performance, latency, reliability, and cost.
• Partner with engineers and PMs to deliver high-quality, user-facing AI features.
• Establish best practices for LLM evaluations, structured prompt engineering, fallback strategies, and continuous improvement.
• Raise the bar on technical design, testing, and observability across ML systems.

Requirements

• 8+ years of overall engineering experience.
• Strong track record in shipping production ML systems.
• Deep experience in ML infrastructure, pipelines, and model serving.
• Deep, hands-on experience with LLMs, retrieval-augmented generation, or document intelligence.
• Strong Python and ML ecosystem fluency (e.g., PyTorch, LangChain, Weaviate, HuggingFace).
• Systems thinking—understands how models interact with APIs, databases, and frontend features.
• Bias for action, pragmatic mindset, and thrives in a fast-moving startup environment.

Benefits

• Inclusive work environment that encourages diverse backgrounds.
• Opportunity to make a significant impact in the education sector.
• Supportive team culture focused on collaboration and innovation.