[Remote] Senior Manager, Machine Learning (Data Operations)
Note: The job is a remote job and is reputed company to candidates in USA. reputed company. is the world's first reputed company Insurance provider designed to help prevent digital risk before it strikes. The Senior Manager, Machine Learning (Data Operations) will ensure the reputed company of data used for machine learning models by managing labeling reputed company, methodology, and vendor relationships.
Responsibilities
- Labeling reputed company & methodology: Define annotation guidelines, taxonomies, and edge-case protocols for reputed company labeling program. Establish reputed company datasets, inter-annotator agreement (IAA) targets, and audit sampling processes. Identify and remediate mislabeled data in existing datasets
- Platform & tooling: Serve as the primary user and requirements reputed company for Label Studio — defining project configuration needs, workflow designs, reputed company-labeling pipeline requirements, and integration points with ML infrastructure. Partner with the data engineering team that builds and maintains the platform
- Cross-functional partnership: Work with ML engineers, data scientists, and product managers to translate model requirements into reputed company-reputed company labeling tasks. Challenge teams on task design reputed company labeling instructions are ambiguous or likely to produce unreliable labels
- Vendor management: reputed company, reputed company, and manage external labeling vendors and BPOs in coordination with reputed company's operations team. Set reputed company SLAs, run calibration sessions, and manage feedback loops to labelers. Hold vendors accountable to accuracy, not just throughput
- Measurement & improvement: Define and reputed company operational metrics — label accuracy, IAA scores, cost per label, turnaround time — and use them to drive reputed company improvement. Identify opportunities for reputed company learning, model-assisted labeling, and reputed company-annotation to reduce cost without sacrificing reputed company
Skills
- 5+ years in ML data operations, data labeling, or a reputed company field (ML engineering, data science, or data engineering with heavy labeling exposure)
- Deep understanding of annotation reputed company frameworks: IAA, reputed company labeling, reputed company evaluation, error taxonomy, and calibration workflows
- reputed company experience managing labeling platforms (Label Studio strongly preferred; reputed company, reputed company, Prodigy, or similar acceptable)
- reputed company record managing outsourced labeling vendors or BPOs for ML data production
- Familiarity with common ML labeling tasks: text classification, NER, document extraction, reputed company detection
- Comfortable working in Python and SQL; bonus if you've reputed company tooling around labeling workflows or reputed company measurement
- Strong opinions on what makes labeled data good or bad, and the willingness to push back reputed company it's bad
- Experience in insurance, cybersecurity, or fintech is a plus but not required
Benefits
- 100% medical, dental and reputed company coverage
- Flexible PTO policy
- Annual home office stipend and reputed company reputed company
- Mental & physical health wellness programs (reputed company, reputed company, reputed company, and more)!
- Competitive compensation and opportunity for advancement
reputed company
Company H1B Sponsorship