Machine Learning Engineer III, Metadata Extraction

boxinc; United States; Hybrid; USD 120,000 - 170,000; Full time

Benefits offered by this job

Hybrid work schedule

Job summary

boxinc is hiring to build and operate machine learning systems that turn complex enterprise documents into structured, usable information. You will work across document understanding, including OCR and language-model-based extraction, from development to production with cross-functional teams.

The role emphasizes strong Python skills, collaboration, and ownership while supporting real-time and batch workloads.

Qualifications

• At least 3 years of experience building, deploying, or operating production software, data, or ML systems.
• Strong Python skills, with readable, testable production code.
• Experience with the lifecycle of language-model-based agents, including data prep and prompting.
• Clear communication, collaboration, and ownership mindset for ambiguous problems.

Responsibilities

• Develop, deploy, and maintain ML models, language model agents, and supporting services.
• Build data prep pipelines and prompts, tools, and agent workflows for document extraction.
• Measure model quality with evaluation sets, experiments, metrics, and feedback.
• Monitor production systems for reliability, latency, cost, and data/model changes; participate in on-call.
• Design scalable services for real-time and batch workloads; provide tests, docs, and runbooks.
• Collaborate with partner teams to translate customer needs into production capabilities.

Skills

Python

Communication

Collaboration

Ownership mindset

Tools

Kubernetes

Terraform

SQL

Job description

Role overview

Build and operate machine learning systems that turn complex enterprise documents into structured, usable information. You'll work across document understanding, including OCR and language-model-based extraction, taking capabilities from development and evaluation through production while partnering with engineering, product, data, and infrastructure teams.

Responsibilities

• Develop, deploy, and maintain machine learning models, language model agents, and supporting services.
• Build data preparation pipelines and design prompts, tools, and agent workflows for document extraction.
• Measure and improve model quality through evaluation sets, experiments, metrics, and feedback.
• Monitor production systems for reliability, latency, cost, and changes in data or model behavior; investigate issues and participate in on-call support.
• Help design scalable services for real-time and batch workloads, and provide tests, documentation, and operational runbooks.
• Work with partner teams to shape customer needs into production capabilities and share engineering practices.

Requirements

• At least 3 years of experience building, deploying, or operating production software, data, or machine learning systems.
• Strong Python skills, including writing readable, testable, maintainable production code.
• Practical experience with the lifecycle of language-model-based agents, including data and evaluation preparation and prompting.
• Clear communication with technical and non-technical partners, collaborative working habits, and an ownership mindset for ambiguous problems.

Nice to have

• Experience with MLOps, model monitoring, feature stores, workflow orchestration, or experiment tracking.
• Production generative AI work, such as semantic search or structured extraction, and familiarity with multimodal document processing.
• Experience with a major cloud provider, Kubernetes, Terraform, SQL, or large-scale analytics.
• Background in enterprise software, security, search, retrieval, or content intelligence; mentoring or technical direction experience.

Benefits and work setup

The role follows a hybrid schedule, with at least three days per week in an assigned office. General employee benefits are mentioned, but specific benefit details are not provided.