# Senior Manager, Machine Learning

**Company:** [Coalition Security](https://hotfix.jobs/companies/coalition-security)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $134k – $200k/yr
**Experience:** 5+ years
**Skills:** label studio, Python, SQL, iaa, ner, text classification, document extraction, intent detection, scale ai, labelbox, prodigy, active learning, model-assisted labeling
**Posted:** 2026-07-17

> Senior Manager overseeing ML data operations and labeling quality at Coalition. Define guidelines and metrics, drive Label Studio platform requirements, manage vendors, and partner with ML teams to ensure high-quality labeled datasets for models.

## Job Description

## Responsibilities
- Define annotation guidelines, taxonomies, and edge-case protocols for labeling programs. Establish gold standard datasets, IAA targets, and audit processes. Identify and remediate mislabeled data.
- Serve as primary user and requirements driver for Label Studio, defining project configurations, workflows, pre-labeling pipelines, and ML infrastructure integrations. Partner with data engineering team.
- Collaborate with ML engineers, data scientists, and product managers to translate model requirements into structured labeling tasks. Challenge ambiguous task designs.
- Source, onboard, and manage external labeling vendors and BPOs. Set quality SLAs, run calibration sessions, manage feedback loops, and hold vendors accountable for accuracy.
- Define and track metrics such as label accuracy, IAA scores, cost per label, and turnaround time. Drive improvements via active learning, model-assisted labeling, and pre-annotation.

## Skills and Qualifications
- 5+ years in ML data operations, data labeling, or related field (ML engineering, data science, or data engineering with heavy labeling exposure).
- Deep understanding of annotation quality frameworks: IAA, consensus labeling, gold standard evaluation, error taxonomy, and calibration workflows.
- Direct experience managing labeling platforms (Label Studio strongly preferred; Scale AI, Labelbox, Prodigy, or similar).
- Track record managing outsourced labeling vendors or BPOs for ML data production.
- Familiarity with common ML labeling tasks: text classification, NER, document extraction, intent detection.
- Comfortable working in Python and SQL; bonus for building tooling around labeling workflows or quality measurement.
- Strong opinions on data quality and willingness to push back on poor practices.
- Experience in insurance, cybersecurity, or fintech is a plus.

## Compensation
US base salary ranges from $134400/year to $200000/year depending on geographic market and factors including education, skills, experience, and location.

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