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Amazon Level 7 Jobs in Texas (NOW HIRING)

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment ... Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a ...

Synchrony

VP, Amazon Analytics

Dallas, TX · On-site

The VP, Analytics will lead portfolio analytics for the Amazon Credit and Payment portfolio ... New hires (Level 4-7) must have 9 months of continuous service with the company before they are ...

Amazon

Executive Assistant II - AMZ9953697

Austin, TX · On-site

$78K - $129K/yr

AMAZON.COM SERVICES LLC Offered Position: Executive Assistant II Job Location: Austin, Texas Job ... Complex executive calendar management with detailed scheduling across multiple high-level calendars ...

Amazon

Maintenance Manager

Waco, TX · On-site

Operations is at the heart of Amazon's business. We are known for our speed, accuracy, and ... level initiatives and provide guidance across multiple sites About the team This position operates ...

Amazon

ASIC III - AMZ9802543

Austin, TX · On-site

$174K - $215K/yr

... system level testing and debugging; and (7) experience with Semi-conductor industry Fab production flows. Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female ...

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All JobsAmazon Level 7 JobsAmazon Level 7 Jobs in Texas

Amazon Level 7 information

See Texas salary details

$21.4K

$71.9K

$113.7K

How much do amazon level 7 jobs pay per year?

As of Jul 28, 2026, the average yearly pay for amazon level 7 in Texas is $71,858.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,000.00 and $89,400.00 per year, depending on experience, location, and employer.

Is L7 a senior role at Amazon?

Yes, Amazon Level 7 (L7) is considered a senior role, typically involving significant responsibilities such as leading projects, mentoring teams, and making strategic decisions. It is often regarded as a senior or managerial level within Amazon's job hierarchy, requiring relevant experience and expertise in the field.

What is the difference between Amazon Level 7 vs Amazon Level 6?

AspectAmazon Level 6Amazon Level 7
Required CredentialsBachelor's degree, relevant experienceBachelor's or Master's degree, extensive experience
Work EnvironmentTeam collaboration, project executionLeadership responsibilities, strategic planning
Employer & Industry UsageCommonly used for senior individual contributor rolesUsed for higher-level senior individual contributor roles with more scope

Amazon Level 7 roles typically require more experience and involve greater responsibility than Amazon Level 6 positions. Level 7 employees often lead projects or initiatives, whereas Level 6 focuses on executing tasks within a team. The progression reflects increased expertise, leadership, and strategic impact within Amazon's organizational structure.

What does an L7 at Amazon do?

An L7 at Amazon typically refers to a senior leadership role, such as a senior manager or principal, responsible for overseeing large teams, strategic planning, and high-impact projects. They often lead cross-functional initiatives, make data-driven decisions, and require strong leadership, technical expertise, and experience in their domain.

What are some common challenges faced by employees at Amazon Level 7, and how can new hires prepare for them?

At Amazon Level 7, employees are often tasked with leading large teams and managing complex projects with high visibility. Common challenges include balancing strategic planning with hands-on execution, navigating Amazon’s fast-paced environment, and aligning cross-functional teams toward ambitious goals. New hires can prepare by sharpening their leadership and decision-making skills, familiarizing themselves with Amazon’s leadership principles, and building strong communication channels with stakeholders. Proactive problem-solving and adaptability are key to thriving in this dynamic role.

What is an Amazon Level 7 position?

An Amazon Level 7 position refers to a senior management role within Amazon's corporate job hierarchy. Level 7 employees typically hold titles like Senior Manager or Principal, and are responsible for leading large teams, driving strategic initiatives, and influencing company-wide decisions. These positions require significant experience, leadership skills, and a proven track record of delivering results. Compensation and expectations at Level 7 are notably higher compared to lower levels, reflecting the increased responsibility and impact of these roles.

What are the key skills and qualifications needed to thrive as an Amazon Level 7 Manager, and why are they important?

To thrive as an Amazon Level 7 Manager, you need strong leadership abilities, extensive project management experience, and a track record of delivering results, often supported by a relevant bachelor's or master's degree. Familiarity with data analytics platforms, Amazon's internal tools (such as Quicksight and Tableau), and Lean/Six Sigma certifications are commonly expected. Exceptional communication, stakeholder management, and problem-solving skills help you navigate complex, fast-paced environments and lead large teams. These skills and qualifications are crucial for effectively driving business goals, managing high-impact projects, and fostering team success at Amazon's senior management level.

What is a level 7 salary at Amazon?

A Level 7 at Amazon typically corresponds to a senior managerial or principal role, with salaries ranging from approximately $150,000 to $200,000 annually, depending on location, experience, and performance bonuses. Total compensation may also include stock options and benefits. Salary figures can vary based on the specific team and responsibilities.

How long does it take to get L7 from Amazon?

Reaching Amazon Level 7 typically takes around 8 to 12 years of experience, depending on individual performance, skills, and career progression within the company. Advancement to L7 involves demonstrating leadership, technical expertise, and consistent high performance over time.
What are popular job titles related to Amazon Level 7 jobs in Texas? For Amazon Level 7 jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Amazon Level 7 jobs in Texas look for? The top searched job categories for Amazon Level 7 jobs in Texas are:
What cities in Texas are hiring for Amazon Level 7 jobs? Cities in Texas with the most Amazon Level 7 job openings:
Amazon Level 7 jobs near you
Infographic showing various Amazon Level 7 job openings in Texas as of July 2026, with employment types broken down into 86% Full Time, 7% Part Time, and 7% Contract. Highlights an 72% In-person, 7% Hybrid, and 21% Remote job distribution, with an average salary of $71,858 per year, or $34.5 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Ascentt

Plano, TX • On-site

$100K - $137K/yr

Full-time

Posted 21 days ago

Job description

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring passionate builders to shape the future of industrial intelligence.
Job Title: Senior Machine Learning Engineer
Location: Ann Arbor, Michigan
Experience Level: 7+ Years
Department: Data Science / Engineering
Employment Type: Full-time
About the Role:
We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud environments. The ideal candidate will be a self-starter with strong problem-solving skills and hands-on experience in building and deploying ML models using big data technologies like PySpark and cloud platforms like Amazon SageMaker.
Key Responsibilities:
  • Design, develop, and deploy scalable machine learning models for real-world business problems using structured and unstructured data.
  • Analyze large datasets using PySpark and other distributed computing frameworks to extract insights and prepare features for ML pipelines.
  • Apply a wide range of statistical, machine learning, and deep learning techniques, including but not limited to regression, classification, clustering, time-series forecasting, and NLP.
  • Own end-to-end ML pipelines from data ingestion, preprocessing, training, validation, tuning, and deployment.
  • Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a production-grade environment.
  • Collaborate closely with data engineers, data scientists, and product teams to integrate models with business workflows.
  • Monitor and improve model performance, scalability, and reliability in production.
  • Contribute to setting up and maintaining the ML environment and tooling (including environment configuration, CI/CD pipelines for ML, model versioning, etc.).

Required Qualifications:
  • 7+ years of experience in machine learning, data science, or related fields.
  • Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
  • Hands-on experience with PySpark for big data processing and model development.
  • Proficient in building models on large-scale datasets (terabytes to petabytes).
  • Solid understanding of statistical analysis, probability, hypothesis testing, and experimental design.
  • Experience with Amazon SageMaker (or similar cloud-based ML platforms).
  • Strong knowledge of ML Ops practices including version control, model monitoring, and retraining strategies.
  • Familiarity with containerization (Docker) and CI/CD practices for ML projects is a plus.
  • Excellent communication skills and the ability to clearly explain complex concepts to non-technical stakeholders.

Preferred Qualifications:
  • Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative discipline.
  • Experience with workflow orchestration tools (e.g., Airflow, Kubeflow).
  • Prior experience in domains like Manufacturing, finance, healthcare, or e-commerce is a plus.

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