Own the product lifecycle for AI capabilities, from discovery and requirements to launch and iteration. Define success metrics (offline evaluation and online impact), align cross-functional teams, and operationalize data workflows including training data quality, annotation QA, and human feedback loops such as RLHF and prompt evaluation.
What You Will Do
- Define AI product vision, PRDs, and roadmaps aligned to user problems and business outcomes
- Translate product goals into model objectives, data requirements, and evaluation plans
- Partner with ML engineering, data science, and MLOps to ship reliable inference services and monitor drift/regressions
- Design evaluation frameworks (offline benchmarks and online experiments) including A/B testing and iterative rollouts
- Coordinate human-in-the-loop workflows: data labeling, QA evaluation, prompt evaluation, and RLHF-informed iteration
- Track analytics, error analysis, and model monitoring to drive continuous improvement and responsible AI practices
Required Qualifications
- Mid-Senior experience leading product initiatives with ML/AI components
- Strong requirements writing and ability to define measurable success metrics
- Working knowledge of ML concepts (embeddings, ranking, generative models) and evaluation tradeoffs
- Familiarity with data operations: labeling programs, audits, dataset versioning, and bias analysis
Preferred Qualifications
- Experience with LLM product patterns such as RAG, prompt orchestration, tool use, and guardrails
- Exposure to NLP/computer vision workflows, content safety labeling, and multimodal evaluation
- Experience operating in remote, global, or Brazil-based teams
Compensation
- Competitive hourly rate: $30–$50/hr
- Remote-first collaboration