
Leading company in the retail industry
Lead Machine Learning Operations Engineer - Ad Tech
必备技能
Python
SQL
Airflow
Machine Learning
As the Lead Machine Learning Operations Engineer, you’ll help shape Best Buy’s next‑generation, machine‑learning‑powered Ad Serving platform. You’ll work at the center of real-time decisioning, large‑scale data pipelines, and advanced analytics—driving fast, relevant, high‑performing ad experiences. If you enjoy solving complex ML problems, optimizing systems at scale, and collaborating across engineering teams, this role gives you the impact and visibility you’re looking for.
This role is hybrid, which means you will work some days at our corporate office in Richfield, Minnesota, and some days virtually from home or another non-Best Buy location. The specific work arrangements vary by role and team. The recruiter or hiring manager will provide more details during the hiring process.
What you’ll do- Work at the nexus of ML, data science, data engineering, and ad serving; training, optimizing, and integrating ML models for real-time ad decisioning and bidding.
- Optimize features, ML models, and infrastructure for traceability, observability, quality, freshness, and low latency and scalability of training and inference.
- Manage feature data, ML workflows, and ML models, making use of modern machine learning operations, dashboards, and monitoring for robust and observable life cycle management.
- Conduct deep analytical investigations to uncover insights and drive data informed decisions about ad delivery system operation and performance.
- Participate in on-call rotation and provide operational support for data pipelines and ML-driven ad serving.
- Mentor and coach ML Scientists and Engineers, fostering a culture of learning and technical excellence.
Basic qualifications- Bachelor’s in Machine Learning, Computer Science, Engineering, Mathematics, Physics, or related field; or equivalent combination of relevant professional experience and education
- 5 years of experience in MLOps, including feature stores, model training, deployment, and lifecycle management
- 5 years of experience using Python for data analysis, modeling, or engineering
- 5 years of experience resolving complex production data and model-serving issues
- Experience with SQL and ML workflow orchestration tools
- 2 years of experience working in advertising technology
Preferred qualifications- Master’s or PhD in a quantitative field
- Experience with high-throughput, real-time ML inference systems
- Experience building dashboards that drive actionable insights
- Familiarity with orchestration tools such as Airflow, Flyte, Cloud Composer, or Step Functions
- Experience with distributed compute systems, ML platforms, and modern ML frameworks
- Experience with inference servers and online feature stores
What’s in it for you
We’re committed to helping our people thrive at work and at home. We offer generous benefits that address your total well-being and provide support as you need it, especially during key moments in your life.
Our benefits include:
- Competitive pay
- Generous employee discount
- Physical and mental well-being support
About us
As part of the Best Buy team, you’ll help us fulfill our purpose to enrich lives through technology. We bring that to life every day by humanizing and personalizing tech solutions for every stage of life—in our stores, online, and in customers’ homes.
Our culture is built on deeply supporting and valuing our amazing employees who make it all possible. We’re committed to being a great place to work, where you can unlock unique career possibilities. Above all, we aim to provide a place where you can bring your full, authentic self to work now and into the future. Tomorrow works here.™
Best Buy is an equal opportunity employer.
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关于Best Buy

Best Buy
PublicBest Buy Co., Inc. is an American multinational consumer electronics retailer headquartered in Richfield, Minnesota. Originally founded by Richard M.
10,001+
员工数
Richfield
总部位置
$7.8B
企业估值
评价
10条评价
4.0
10条评价
工作生活平衡
2.8
薪酬
3.2
企业文化
4.1
职业发展
3.7
管理层
2.5
72%
推荐率
优点
Great team environment and support
Good training and comprehensive onboarding
Flexible scheduling options
缺点
Work-life balance challenges and long hours
High stress during peak times and sales events
Pay could be better
薪资范围
12,325个数据点
L2
L6
M3
M4
M5
M6
Mid/L4
Senior/L5
L3
L4
L5
L2 · Data Scientist L2
0份报告
$94,250
年薪总额
基本工资
$37,700
股票
$47,125
奖金
$9,425
$65,975
$122,525
面试评价
4条评价
难度
3.0
/ 5
时长
21-35周
录用率
50%
体验
正面 0%
中性 25%
负面 75%
面试流程
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-Person Interview
5
Offer
常见问题
Behavioral/STAR
Past Experience
Culture Fit
Customer Service Scenarios
最新动态
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