4 дня назад
Applied Scientist (AI Evaluation and Data Strategy)
160 000 - 170 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Applied Scientist (AI Evaluation and Data Strategy) (AI/Computer Vision): Defining evaluation strategies, reproducible pipelines, and data-improvement loops for advanced AI, vision, perception, and generative systems with an accent on model quality, robustness, controllability, coverage, and downstream utility. Focus on analyzing model artifacts, identifying hidden failure patterns, designing statistically sound comparisons, and translating evidence into production-readiness decisions.
Location: Remote from the United States
Salary: $160,000–$170,000 per year, plus eligibility for an annual performance bonus.
Company
is a location data and technology platform company that helps cities manage infrastructure, businesses optimize assets, and drivers navigate safely.
What you will do
- Define evaluation strategies, metrics, test sets, and release gates for advanced AI, vision, and perception capabilities.
- Build reproducible evaluation pipelines covering model quality, robustness, controllability, coverage, and downstream utility.
- Analyze model outputs and artifacts to identify failure patterns that aggregate metrics miss.
- Design dataset audits, gap analyses, sampling strategies, and targeted data acquisition or generation loops.
- Partner with scientists and engineers on experiment design, benchmarking, and statistically sound comparisons.
- Communicate evidence, tradeoffs, and model-readiness recommendations to technical and product stakeholders.
Requirements
- Strong experience evaluating machine-learning, computer-vision, multimodal, or generative-AI systems.
- Advanced Python and SQL skills with experience building scalable analysis or evaluation workflows.
- Strong foundations in statistics, experimental design, error analysis, and model validation.
- Ability to turn ambiguous quality questions into measurable criteria and actionable decisions.
- Ability to inspect model outputs deeply, identify patterns, and explain required improvements.
- Technical leadership skills and the ability to influence data science, engineering, and product teams.
Nice to have
- Experience with spatial, geospatial, sensor, map, trajectory, or simulation data.
- Experience evaluating generative models, temporal consistency, or perception systems.
- Familiarity with data-centric AI, active learning, synthetic data, or human-evaluation programs.
- Graduate degree in a quantitative or technical discipline.
Culture & Benefits
- Medical, dental, and vision insurance for US-based employees.
- Retirement savings plans.
- Paid time off and leave policies.
- Background verification is required as part of the employment process.
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