This role exists to build, scale, and operationalize Dollar General's enterprise machine learning capabilities that directly drive measurable business outcomes. The Senior Director owns the ML ...
This role exists to build, scale, and operationalize Dollar General's enterprise machine learning capabilities that directly drive measurable business outcomes. The Senior Director owns the ML ...
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Senior Meta Machine Learning information
Is L7 senior at Google?
How much does L7 make at Meta?
What engineer makes $500,000 a year?
What is the difference between Senior Meta Machine Learning vs Data Scientist?
| Aspect | Senior Meta Machine Learning | Data Scientist |
|---|---|---|
| Required Credentials | Master's or PhD in CS, ML, or related fields; experience with meta-learning frameworks | Bachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis |
| Work Environment | Research-focused teams developing advanced ML models, often in AI companies | Data analysis, modeling, and visualization across various industries |
| Employer & Industry Usage | Tech firms, AI startups, research institutions | Finance, healthcare, e-commerce, tech companies |
While both roles involve machine learning expertise, Senior Meta Machine Learning specialists focus on developing advanced meta-learning algorithms, often in research settings, whereas Data Scientists apply data analysis and modeling techniques across diverse industries. The roles share similar educational backgrounds but differ in focus and application.
How much does a Meta senior machine learning engineer make?
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Full-time
Posted 26 days ago
Dollar General rating
4.0
Based on 4,478 frontline employees who took The Breakroom Quiz
39th of 39 rated national retailers
Job description
Company Overview
General Summary:
This role exists to build, scale, and operationalize Dollar General’s enterprise machine learning capabilities that directly drive measurable business outcomes. The Senior Director owns the ML strategy, platforms, and teams required to move from isolated models to production-grade, governed, reusable ML systems. This leader ensures ML investments are aligned to enterprise priorities, value realization, and responsible AI standards.
Job Details
Duties and Responsibilities:
- Lead enterprise machine learning strategy spanning applied ML, MLOps, experimentation, and platform capabilities aligned to business priorities.
- Build, mentor, and scale high-performing ML engineering and data science leaders across centralized and embedded delivery models
- Own end-to-end lifecycle of ML systems from problem framing and modeling through deployment, monitoring, and continuous optimization
- Partner with product, IT, security, legal, and business leaders to ensure governed, responsible, and scalable ML adoption.
- Establish standards for model evaluation, experimentation, monitoring, and value measurement tied to financial and operational impact
Qualifications
Knowledge, Skills and Abilities:
- Deep expertise in machine learning systems, model development, and production ML architectures
- Strong understanding of MLOps, model monitoring, experimentation, and CI/CD for ML
- Proven ability to translate business problems into scalable ML solutions with measurable impact
- Experience leading senior technical managers and principal-level engineers
- Strong judgment around responsible AI, model risk, data privacy, and governance
- Ability to influence executive stakeholders and align cross-functional teams
- Experience operating ML platforms in cloud-native environments
- Excellent communication skills bridging technical and non-technical audiences
Work Experience and/or Education:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
- Advanced degree (Master’s / MBA) in a quantitative or AI-related discipline preferred
- 10+ years of experience in machine learning, data science, or applied AI roles
- 5+ years leading ML engineering or data science teams at scale
- Demonstrated experience deploying and operating production ML systems
Experience in retail, e-commerce, supply chain, or large-scale consumer data environments preferred
Qualifications:Knowledge, Skills and Abilities:
- Deep expertise in machine learning systems, model development, and production ML architectures
- Strong understanding of MLOps, model monitoring, experimentation, and CI/CD for ML
- Proven ability to translate business problems into scalable ML solutions with measurable impact
- Experience leading senior technical managers and principal-level engineers
- Strong judgment around responsible AI, model risk, data privacy, and governance
- Ability to influence executive stakeholders and align cross-functional teams
- Experience operating ML platforms in cloud-native environments
- Excellent communication skills bridging technical and non-technical audiences
Work Experience and/or Education:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
- Advanced degree (Master’s / MBA) in a quantitative or AI-related discipline preferred
- 10+ years of experience in machine learning, data science, or applied AI roles
- 5+ years leading ML engineering or data science teams at scale
- Demonstrated experience deploying and operating production ML systems
Experience in retail, e-commerce, supply chain, or large-scale consumer data environments preferred
Education:UNAVAILABLEEmployment Type: FULL_TIMEWhat Dollar General employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Dollar General
Sourced by ZipRecruiter
What started as a single store is now a 20+ billion dollar Fortune 119 company. With 140,000+ employees and counting, we’re growing fast and so can you. There are endless opportunities for you, including award-winning training programs and career paths in retail, distribution, transportation or corporate. The possibilities are endless!
Industry
Retail
Company size
10,000+ Employees
Headquarters location
Goodlettsville, TN, US