赤峰QA品质工程师
QA品质工程师是负责质量保证和质量控制的专业人士。他们负责制定和执行测试计划,评估产品性能,发现和解决质量问题。QA品质工程师需要对产品进行严格的测试和分析,确保产品符合质量标准和客户需求。他们还需要与开发团队和其他部门紧密合作,共同解决产品质量问题。此外,QA品质工程师还负责编写质量报告和文件,并提出改进建议以持续改进产品质量。总之,QA品质工程师在确保产品质量和客户满意度方面发挥着关键作用。他们需要具备严谨的分析能力、沟通技巧和团队合作精神。
薪酬概览
平均月薪
¥5200
中位数 ¥4500 | 区间 ¥3800 - ¥6600
数据来源:样本数量过少,仅供参考;更新时间:2026年7月13日
月薪分布
100% 人群薪酬落在 0-8k

三大影响薪酬的核心维度
影响薪资的核心维度1:工作年限
影响薪资的核心维度2:学历背景
市场需求
6月新增岗位
14
对比上月:岗位新增10
数据由各大平台公开数据统计分析而来,仅供参考。
岗位需求趋势
不同经验岗位需求情况
| 工作年限 | 月度新增职位数 | 职位占比数 |
|---|---|---|
| 1-3年 | 2 | 33.3% |
| 3-5年 | 2 | 33.3% |
| 不限经验 | 2 | 33.3% |
热招职位
1. 负责核心连锁客户的任务谈判和日常跟进,三九品种的进场以及制定可操作的连锁活动,实现上量。
2. 备案连锁重点门店,完成备案门店的客情维护、驻店销售、贴柜培训,仪器检测,产品陈列等门店下沉工作,并对备案门店的产出负责。
3. 积极执行总部主题活动,同时协助区域领导帮助核心连锁客户做核心产品的上量活动。
1、协助区域开展销售工作,实战销售一线业务;
2、协助区域开展消费者营销工作;
3、多维度分析区域数据,协助上级制定销售策略;
4、负责校园招聘项目推广工作。该岗位设置实习期,实习期通过后可转正。
1、在指定区域内开展公司产品推广活动,传达医学信息,以合法合规方式达成公司指标;
2、根据需要拜访客户,配合医学市场部的计划组织开展学术会议,传递最新产品信息;
3、开拓潜在医院渠道客户,并对既有客户进行维护,与客户建立良好关系;
4、及时收集、提供市场信息并做出适当建议;
5、确保日常工作符合公司合规政策、行业准则及法律法规;
6、完成上级交办的其他工作。
1、根据区域渠道及产品布局与经销商签订合同,并严格执行,确保销售目标达成;
2、协助经销商开发、维护零售商并建立零售商档案;协助经销商制定分产品的零售商渠道规划,管理和规范零售商行为;
3、负责经销商区域的试验示范以及零售商、大农户等层面的需求拉动活动的开展;
4、培训零售经销商进行种植户的产品推荐及相应的农技方案;
5、完成大丰产品在所辖区域零售经销商的铺货、促销及库存管理,确保零售和库存数据的有效性;
6、销售主管除完成以上任务外,根据省区经理的授权,负责部分经销商的筛选和评估工作。
1、合规化工作的的规划、落实与执行;
2、协助区域拟定基础销售管理流程、合规化的执行流程和相关内部管理的规定,并跟进发布执行;
3、客户数据与运营指标的数据分析;
4、处理区域内债权保障相应工作,落实合同、协议的签收记录,处理客户发票签收与货物签收,定期催收对账函及跟进处理差异情况。
1. 管理区域客户,负责区域客户销售目标的设定及跟踪完成;
2. 指导客户做好渠道建设、管理、考核等工作;
3. 指导客户做好产品试验示范及市场推广活动;
4. 协调和执行区域内跨部门活动,如试验示范、市场活动、抱怨处理等;
5. 负责市场信息的收集、整理、分析与反馈;
6. 支持销售大区总监完成区域内或跨部门协同工作。
- Responsible for product experience operations, including establishing product experience mechanism standards, building an experience metrics system, and enhancing experience operation capabilities.
- Monitor data trends and anomalies to proactively identify product quality issues, user experience gaps, or system inefficiencies.
- Establish a data monitoring mechanism, perform daily data extraction, analysis, and visualization using tools such as SQL to identify operational bottlenecks and risk points.
- Build strong collaborative working mechanisms with business teams and establish an effective closed-loop process with internal service teams to jointly improve operational outcomes.
任职资格
- Educational Background: Full-time bachelor's degree or higher.
- Work Experience: Over 3 years of experience in data analysis, data product management, or data engineering. Experience in SQL is needed.
- Professional Skills: Strong understanding of data architecture and quality assurance processes; excellent data mining, analysis, and visualization skills; experience in defining and managing KPIs for AI service or digital products.
- Soft Skills: Excellent communication, execution, and cross-team collaboration skills; strong problem-solving and logical thinking abilities.
- Language Skills: Proficiency in written and spoken English.
- Preferred Qualifications: Project management experience is a plus.
- AI Quality Assessment Framework & Standards
- Establish and maintain quality evaluation criteria for LLMs, covering accuracy, safety, compliance, and instruction-following capabilities.
- Design evaluation workflows combining automation and human-in-the-loop assessment to quantify model performance regularly.
- End-to-End Quality Control & Risk Management
- Own regression testing and acceptance testing for model iterations, enforcing quality gates to prevent performance degradation before launch.
- Monitor online performance to mine for badcases, identifying model hallucinations, logic errors, or experience defects, and issue timely risk alerts.
- Issue-Driven Improvement & Closed-Loop Management
- Lead Root Cause Analysis for quality issues, precisely diagnosing whether failures stem from data, prompts, or model architecture.
- Drive algorithm, product, and operations teams to resolve quality defects, track the fix rate and conduct re-validation to ensure a closed-loop process.
- Cross-functional Collaboration
- Bridge the gap between business needs and technical implementation, ensuring the AI delivers real value to users.
任职资格
- Educational Background: Full-time bachelor's degree or higher.
- Work Experience: 3+ years of experience in internet product operations. Hands-on experience in LLM/AIGC product operations is highly preferred.
- Professional Skills:
- Mastery of AI evaluation methodologies (e.g., Golden Dataset construction, Human Evaluation SOPs).
- Sharp eye for detail ("bug hunting" mindset) with the ability to mine potential risks from massive data.
- Familiarity with Prompt Engineering to reproduce or verify issues (focus on validation rather than daily maintenance).
- Soft Skills: Strong cross-functional communication skills; ability to use data to influence and drive cross-functional partners to solve complex problems.
- Language Skills: Proficiency in written and spoken English.
- Preferred Qualifications: Project management experience is a plus.
1、负责产品全生命周期质量管理工作,确保产品高质高效交付;
2、基于IPD流程及产品特点,能够根据产品特点完成产品维度及专项维度质量策划、组织项目TR节点评审、质量复盘等工作;
3、深入产品开发过程,通过质量度量、分析、评估等,识别产品质量问题和风险,提供解决方案并驱动持续改进;
4、对问题敏感,能够及时发现问题并推动解决;
5、负责领域质量工程建设:进行质量专项能力、专业方法的研究和落地;
6、负责领域的流程建设:完成产品开发流程在项目的适配、试点和推行,并通过研发活动中发现的问题、优秀实践,驱动流程优化;
7、配合公司/业务需求,支持内外部审核。
从事实验室测试用光电设备研发工作,实验室光学镜头、投影机等产品光电性能检测工作,光学镜头、监控摄像机、投影机等产品光电性能检测方法和技术研究工作。
岗位职责:
1)负责对接业务线的质量管理工作,根据业务流程变化和外部环境变化搭建和完善质量指标体系和配套制度流程,运用监控报表、调研、体验测试、案例抽检等多方式监控、分析和统计业务线客户相关质量表现;
2)基于识别到的质量问题进行单点和整体分析,思考提出并主导用户体验优化专项和内部流程质量改进专项;
3)结合客户声音和竞品动向,运用问卷调查、电话访谈等多种方法进行专题用户体验研究,向业务团队输出有价值的问题改进建议和增值优化建议;
4) 掌握客户体验和金融消费者权益保护的相关标准、原则和具体要求,独立开展对接业务线的质量审核;
5) 持续追踪落实相关业务团队对质量问题和质量建议的改进落实。
任职资格
岗位要求:
1) 理解质量管理在对客体验和对内流程上的标准,了解金融消费者权益保护相关原则性要求,在银行、支付机构、互金机构等金融相关岗位或用户体验研究相关岗位有工作经验优先;
2) 具备良好的主动思考和独立判断能力,具备良好的数据分析能力,逻辑清晰;具备良好的沟通表达和协调推进能力;
3) 细致稳重,责任感强,对待改进项有敏锐的识别能力;
4) 熟练运用Excel, PPT, Word等日常办公软件,英语CET-6,口语表达流利者优先。
Senior QA EN SHACC ALL(MJ035074)
- AI Quality Assessment Framework & Standards
- Establish and maintain quality evaluation criteria for LLMs, covering accuracy, safety, compliance, and instruction-following capabilities.
- Design evaluation workflows combining automation and human-in-the-loop assessment to quantify model performance regularly.
- End-to-End Quality Control & Risk Management
- Own regression testing and acceptance testing for model iterations, enforcing quality gates to prevent performance degradation before launch.
- Monitor online performance to mine for badcases, identifying model hallucinations, logic errors, or experience defects, and issue timely risk alerts.
- Issue-Driven Improvement & Closed-Loop Management
- Lead Root Cause Analysis for quality issues, precisely diagnosing whether failures stem from data, prompts, or model architecture.
- Drive algorithm, product, and operations teams to resolve quality defects, track the fix rate and conduct re-validation to ensure a closed-loop process.
- Cross-functional Collaboration
- Bridge the gap between business needs and technical implementation, ensuring the AI delivers real value to users.
任职资格
- Educational Background: Full-time bachelor's degree or higher.
- Work Experience: 3+ years of experience in internet product operations. Hands-on experience in LLM/AIGC product operations is highly preferred.
- Professional Skills:
- Mastery of AI evaluation methodologies (e.g., Golden Dataset construction, Human Evaluation SOPs).
- Sharp eye for detail ("bug hunting" mindset) with the ability to mine potential risks from massive data.
- Familiarity with Prompt Engineering to reproduce or verify issues (focus on validation rather than daily maintenance).
- Soft Skills: Strong cross-functional communication skills; ability to use data to influence and drive cross-functional partners to solve complex problems.
- Language Skills: Proficiency in written and spoken English.
- Preferred Qualifications: Project management experience is a plus.

