Data & AI Program Manager

Cyborg Mobile•Redmond, WA

1d•Remote

About The Position

We're hiring a Data & AI Program Manager to support a Fortune 100 technology company. This role sits at the intersection of data strategy and applied machine learning, owning the end-to-end data lifecycle that fuels natural language processing (NLP) applications and large language model (LLM) development. You'll define what "good data" looks like for a range of NLP use cases, build the guidelines and pipelines to get there, and partner closely with data engineering, data science, and ML teams to turn high-quality annotated data into measurable model performance gains. This is a full-time position (W2 or 1099 is fine). You would be employed by Cyborg Mobile but placed with our client working full-time there and reporting to a manager there. We're looking for someone who is a self-starter, self-sufficient, and able to execute with little direction. This is a remote position (Washington candidates preferred).

Requirements

Experience in NLP data strategy, annotation program management, or a related data quality/linguistics role
Strong understanding of data annotation workflows, guideline design, and inter-annotator quality control
Familiarity with LLM training/fine-tuning pipelines and how annotated data feeds model evaluation
Analytical mindset with the ability to translate quality metrics into concrete improvement plans
Excellent stakeholder communication skills — comfortable presenting to both technical and non-technical audiences
Experience working in large, matrixed corporate environments
Customer centric
Good with follow through
Has skills to build Agents, PowerBI dashboards, Sharepoint list management, coding agents like Codex, Claude Code, Github copilot

Responsibilities

Conduct market and user research to understand data needs and expectations across various NLP applications and domains
Define data specifications, scope, and sourcing strategy for each use case and domain
Design judgment guidelines and instructions for data annotation, validation, and quality control
Deliver datasets, schemas, guidelines, and annotations that meet approved specifications, scope, and sourcing requirements
Manage the end-to-end data annotation process
Analyze data quality metrics (accuracy, consistency, coverage, and diversity) and turn findings into actionable recommendations
Implement approved data quality improvement actions
Collaborate with client data engineers, data scientists, and machine learning engineers to integrate annotated data into production pipelines, support LLM fine-tuning, and evaluate model performance and impact
Identify data gaps and opportunities; propose new data sources, methods, and features to improve data quality and model outcomes
Communicate data vision, strategy, and results to internal and external stakeholders, including product owners, engineers, researchers, customers, and partners
Prepare and deliver data reports, presentations, and demos using client-approved formats and channels