酷澎
Staff Machine Learning Engineer 2, Ads
Staff Machine Learning Engineer 2, Ads
发布于 大约 2 个月前普通员工/个人贡献者
Mountain View, USA
高级经验
全职员工
仅现场办公
本科
软件工程
PyTorch
TensorFlow
Machine Learning
AI 估算 · 98k–169k
Staff level at top e-commerce company with specialized ML skills, market competitive for Silicon Valley area.
职位详情
关于这个职位
As a Staff Machine Learning Engineer at Coupang's Ads Quality team, you will design and build large-scale ML models and systems to power advertising targeting, relevance, and ranking. You will work on cutting-edge technologies such as transformer models, contrastive learning, and vector search to improve ad performance and user experience. This role offers the opportunity to impact a rapidly growing ad platform handling over 1 billion daily impressions, with competitive compensation and equity.
最低要求
Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
years of professional experience in applied machine learning
Experience in machine learning, deep learning, and statistical modeling
Proficiency in Python and/or Java, with experience in building production grade ML systems
工作职责
Design features and build large-scale machine learning models and systems to improve ad targeting, relevance, ranking, and engagement
Design and implement large-scale ML systems for search ranking, semantic retrieval, query understanding, and personalized product discovery using state-of-the-art techniques such as transformer-based models, contrastive learning, and vector search
Drive innovation in search relevance and user intent modeling using large language models (LLMs), embedding-based retrieval, and multi-modal learning
Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow, ensuring reproducibility, scalability, and operational excellence
Define and track key performance metrics to evaluate model impact and identify high-leverage opportunities for improvement
Collaborate cross-functionally with product, engineering, and data science teams to align technical solutions with business goals and customer experience
Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning
优先资格
Master’s or PhD in relevant technical fields
Experience with search systems, information retrieval or recommendation engines
Experience with LLMs, embeddings, and vector search technologies
Experience with cloud platforms such as AWS, Google Cloud Platform including services like Vertex AI, BigQuery or SageMaker
Experience working in startup or high-growth environments
Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM, and H2o.ai
Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker
Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
Demonstrated ability to work independently and manage ambiguity in fast-paced environments
AI 洞察
优缺点分析
优点
- High impact role in a rapidly growing ad platform with 1B daily impressions, offering significant revenue potential.
- Exposure to cutting-edge ML techniques (LLMs, transformer, vector search) that are in high demand.
- Competitive compensation including base salary up to $282K plus bonus and equity.
- Fast-paced environment may require handling ambiguity and tight deadlines.
- Working in a relatively new ad organization requires building processes from growth to enterprise scale.
- An experienced ML engineer who thrives on building large-scale systems, enjoys innovation, and wants to impact a high-growth advertising business.
缺点 / 挑战
暂无明显挑战项
角色解读
- Progress to Principal or Distinguished ML Engineer, leading more complex ad system innovations.
- Transition into technical leadership roles managing teams of ML engineers.
- Expand into broader AI roles in e-commerce, recommendation, or search domains.
- Design and develop large-scale machine learning models for ad targeting, ranking, and relevance.
- Implement state-of-the-art ML systems including transformer models, contrastive learning, and vector search.
- Optimize ML pipelines using tools like Spark, Airflow, and Kubeflow for scalability and operational excellence.
- Collaborate with product, engineering, and data science teams to align technical solutions with business goals.
- Strong foundation in machine learning, deep learning, and statistical modeling.
- Proficiency in Python and/or Java with experience building production-grade ML systems.
- Experience with modern ML frameworks (TensorFlow, PyTorch) and lifecycle tools (MLflow, Kubeflow).
- Knowledge of search systems, retrieval, and vector search technologies is preferred.
申请策略
- Learn about Coupang's ad platform growth and the unique challenges of the Korean e-commerce market.
- Demonstrate your ability to work cross-functionally and communicate technical concepts to non-technical stakeholders.
- Emphasize hands-on experience with large-scale ML systems and production deployment.
- Highlight projects involving ad ranking, search, or recommendation systems.
- Showcase proficiency with Python, TensorFlow/PyTorch, and cloud platforms (AWS/GCP).
- Deepen knowledge of transformer models, embeddings, and vector databases.
- Build experience with ML pipeline orchestration tools like Kubeflow or Airflow.
面试指南
- Use STAR (Situation, Task, Action, Result) to structure your experiences.
- Focus on trade-offs: accuracy vs. latency, complexity vs. maintainability.
- Show data-driven decision making by explaining how you evaluated model improvements via offline metrics and A/B tests.
- Describe a large-scale ML system you designed and its impact on business metrics.
- How would you approach building a real-time ad ranking model with millions of features?
- Explain contrastive learning and how you would apply it to ad relevance.
- How do you handle feature engineering and model serving for high-throughput systems?
- Tell us about a time you mentored a junior engineer and improved team processes.
职位点评
76
综合评分
High-growth ad tech role with cutting-edge ML, strong compensation, limited remote flexibility.
更适合这类人
This role is ideal for candidates highly motivated by technical growth and innovation, who are comfortable with on-site work and a fast-paced environment.
表现最好
成长发展
相对薄弱
工作生活
薪资福利85
成长发展90
工作生活60
使命价值70
薪资福利
85较高
Compensation is highly competitive with base salary up to $282K plus bonus and equity, typical for top tech companies in the Bay Area. Benefits include comprehensive insurance, 401K match, PTO, and parental leave.
薪资信号偏高 (98K-169K/月)
福利待遇Medical/Dental/Vision/Life, AD&D insurance、Flexible Spending Accounts (FSA) & Health Savings Account (HSA)、Long-term/Short-term Disability、Employee Assistance Program (EAP)、401K Plan with Company Match、18-21 days of Paid Time Off (PTO) a year、12 Public Holidays、6 weeks Paid Parental leave、Pre-tax commuter benefits、Electric Car Charging Station
成长发展
90较高
The role offers immense growth potential through cutting-edge ML projects (LLMs, vector search, transformer models) and mentorship opportunities. The company is in a growth phase, providing career advancement in a high-revenue area.
技术前沿前沿/新兴技术
技术栈Machine Learning、Deep Learning、Transformer、Contrastive Learning、Vector Search、LLM、Apache Spark、Airflow、Kubeflow、MLflow、TensorFlow、PyTorch
业务类型profit_center
工作生活
60中等
Work is on-site in Mountain View, CA, with no explicit remote or hybrid flexibility mentioned. Benefits like PTO and parental leave are standard for US tech companies. No indication of overtime culture, but typical for high-growth ad teams.
工作模式仅现场办公
办公地点海外（不适用）
加班情况未提及（无法判断）
使命价值
70中等
Working on advertising technology at a rapidly growing e-commerce company provides a sense of impact on business growth and customer experience. The role contributes to disrupting the e-commerce industry, but social impact is neutral.
行业发展高速增长赛道
社会影响中性/一般
使命信号wow our customers、disrupting the multi-billion dollar e-commerce industry
创新程度积极采用新技术
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