Lead Data Scientist
什么是角色?我们正在聘请一个领先的数据科学家来拥有应用 AI 质量,数据策略和在高级人工智能,计算机视觉和感知系统中下游有用性。这个人将定义我们如何确定系统是否运行,它在哪里失败,发布需要什么质量条格以及数据,评估和应用建模应该如何发展以改善产品。这是能够为不明确技术计划带来严谨程度,建立评估系统并将模型行为转化成产品决策,数据战略和具体改进循环的人员的一项高级职位。你将拥有什么?- 对先进的人工智能和视觉系统进行评估框架和质量战略- 为输出质量,结构性忠诚度,时间一致性,标签质量,强度和运营可重复性定义通过/失败指标- 为了提高模型质量和下游有用性的数据和验证策略- 领导对文物审计,失败分类学开发,发布质量的报告和基于证据的优先级测量- 衡量产品是否适合感知,绘图,生成人工智能以及面向客户使用情况- 与模型,模拟和平台所有者合作推动质量改善和生产准备决策 定义人为审查协议和复杂人工智能系统的产品接受门-评估出口是否保持下游应用程序预期的结构,语义学和一致性-将评价结果转化为数据策略,实验优先级和应用建模机会-帮助确定数据集设计,验证片段和质量改善循环在整个产品中-创建并发布报告将技术输出的转化成明确的产品决策-帮助优先考虑团队应该基于证据而不是直觉来解决什么问题 - 建立 评估基础在未来的 AI,感知和绘图能力中仍然有用 你是谁?我们正在寻找什么 - 在应用机器学习,计算机视觉,合成数据评价或感知系统验证方面具有强的背景- 对生成性,仿真或感知体系进行测量和评估框架的设计经验- 在模拟或感知系統中的模型行为,数据质量和产品结果联系的经验- 翻译的能力
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What's the role?
We are hiring a Lead Data Scientist to own applied AI quality, data strategy, and downstream usefulness across advanced AI, computer vision, and perception systems. This person will define how we determine whether a system is working, where it is failing, what quality bar is required for release, and how data, evaluation, and applied modeling should evolve to improve the product. This is a senior role for someone who can bring rigor to ambiguous technical programs, establish evaluation systems, and translate model behavior into product decisions, data strategy, and concrete improvement loops. What You Will Own- Own the evaluation framework and quality strategy for advanced AI and vision systems- Define pass/fail metrics for output quality, structural fidelity, temporal consistency, label quality, robustness, and operational repeatability- Own data and validation strategy for improving model quality and downstream usefulness- Lead artifact auditing, failure taxonomy development, release-quality reporting, and evidence-based prioritization- Measure whether outputs are suitable for perception, mapping, generative AI, and customer-facing use cases- Partner with model, simulation, and platform owners to drive quality improvements and production-readiness decisions What You Will Do- Build and evolve metric suites for output quality, fidelity, repeatability, and downstream usefulness- Define human-review protocols and product acceptance thresholds for complex AI systems- Evaluate whether outputs preserve the structure, semantics, and consistency expected by downstream applications- Translate evaluation findings into data strategy, experiment priorities, and applied modeling opportunities- Help define dataset design, validation slices, and quality-improvement loops across the product- Create experiment and release reports that turn technical output into clear product decisions- Help prioritize what the team should fix next based on evidence rather than intuition- Establish evaluation foundations that remain useful across future AI, perception, and mapping capabilitiesWho are you?
What We Are Looking For - Strong background in applied machine learning, computer vision, synthetic-data evaluation, or perception-system validation- Experience designing metrics and evaluation frameworks for generative, simulation, or perception systems- Experience connecting model behavior, data quality, and product outcomes in ambiguous AI systems- Ability to translate research-quality experiments into practical engineering and release decisions- Strong analytical judgment and clear written communication- Comfort owning both strategy and execution in a small team Education & Experience
- Master’s or PhD in Computer Science, AI, Machine Learning, or related field.- 5-8 years of experience in deep learning, computer vision, or multimodal AI.
Nice To Have- Experience with simulation, autonomous systems, geospatial AI, or map-grounded perception tasks- Familiarity with video quality metrics, structural similarity measures, temporal consistency checks, segmentation and detection evaluation, or label-quality assessment- Experience assessing synthetic-to-real transfer, dataset usefulness for downstream models, data curation strategy, or production quality governance The expected base salary range for this position is $160,000 to $170,000 per year. Actual compensation will be based on factors such as skills and experience. This position is also eligible for an annual performance bonus, which is subject to company and individual performance.
Life at HERE comes with generous benefits to support your health and overall wellness. Benefits available to US-based HERE employees include health (Medical/Dental/Vision) insurance, retirement savings plans, paid time off & leave policies.
As part of HERE Technologies employment process, candidates will be required to successfully complete a background verification process. Offers of employment and any related claims are subject to the successful completion of a background verification. Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, HERE will consider for employment qualified applicants with arrest and conviction records.
HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics.
Under Section 503 of the Rehabilitation Act of 1973 and VEVRAA, we have developed an affirmative action program (AAP) for individuals with disabilities and protected veterans. Portions of the AAP are available for review by applicants and employees through our People Team.
Who are we?
HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely.
At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel.
Originally posted on Himalayas