
Leading company in the retail industry
Lead Machine Learning Operations Engineer - Ad Tech
필수 스킬
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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Best Buy 소개

Best Buy
PublicBest Buy Co., Inc. is an American multinational consumer electronics retailer headquartered in Richfield, Minnesota. Originally founded by Richard M.
10,001+
직원 수
Richfield
본사 위치
$7.8B
기업 가치
리뷰
10개 리뷰
4.0
10개 리뷰
워라밸
2.8
보상
3.2
문화
4.1
커리어
3.7
경영진
2.5
72%
지인 추천률
장점
Great team environment and support
Good training and comprehensive onboarding
Flexible scheduling options
단점
Work-life balance challenges and long hours
High stress during peak times and sales events
Pay could be better
연봉 정보
12,325개 데이터
L2
L6
M3
M4
M5
M6
Mid/L4
Senior/L5
L3
L4
L5
L2 · Data Scientist L2
0개 리포트
$94,250
총 연봉
기본급
$37,700
주식
$47,125
보너스
$9,425
$65,975
$122,525
면접 후기
후기 4개
난이도
3.0
/ 5
소요 기간
21-35주
합격률
50%
경험
긍정 0%
보통 25%
부정 75%
면접 과정
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-Person Interview
5
Offer
자주 나오는 질문
Behavioral/STAR
Past Experience
Culture Fit
Customer Service Scenarios
최근 소식
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