Description
- 2+ years of people management experience
- 3+ years of managing stakeholders in cross-functional project experience
- Bachelor's degree in Math, Statistics, Computer Science, or related science field, or Bachelor's degree and 1+ years of data scientist experience
- Bachelor's degree in operations research, applied mathematics, theoretical computer science, or equivalent, or experience in a ML or data scientist role with a large technology company
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience with data annotation workflows and quality assurance processes
- Master's degree in a related technical field
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- Experience building web based dashboards using common frameworks
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon Quick is seeking an experienced ML Data Ops Manager to lead our data operations team supporting machine learning initiatives across the Quick Suite features. This role will manage a team of data associates responsible for data quality, annotation workflows, and operational excellence
Key job responsibilities
Manage and mentor a team of data associates supporting ML model development and evaluation.
Build team capabilities in data annotation, quality assessment, and operational workflows.
Establish performance metrics and conduct regular performance reviews.
Provide regular reporting on data operations status to leadership.
Identify patterns and insights from data quality analysis to drive improvements.
Support MBR preparation with data-driven insights and recommendations.
Design and implement automation opportunities to improve operational efficiency.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
- 3+ years of managing stakeholders in cross-functional project experience
- Bachelor's degree in Math, Statistics, Computer Science, or related science field, or Bachelor's degree and 1+ years of data scientist experience
- Bachelor's degree in operations research, applied mathematics, theoretical computer science, or equivalent, or experience in a ML or data scientist role with a large technology company
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience with data annotation workflows and quality assurance processes
- Master's degree in a related technical field
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- Experience building web based dashboards using common frameworks
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon Quick is seeking an experienced ML Data Ops Manager to lead our data operations team supporting machine learning initiatives across the Quick Suite features. This role will manage a team of data associates responsible for data quality, annotation workflows, and operational excellence
Key job responsibilities
Manage and mentor a team of data associates supporting ML model development and evaluation.
Build team capabilities in data annotation, quality assessment, and operational workflows.
Establish performance metrics and conduct regular performance reviews.
Provide regular reporting on data operations status to leadership.
Identify patterns and insights from data quality analysis to drive improvements.
Support MBR preparation with data-driven insights and recommendations.
Design and implement automation opportunities to improve operational efficiency.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
There are more than 50,000 engineering jobs:
Subscribe to membership and unlock all jobs
Engineering Jobs
60,000+ jobs from 4,500+ well-funded companies
Updated Daily
New jobs are added every day as companies post them
Refined Search
Use filters like skill, location, etc to narrow results
Become a member
🥳🥳🥳 452 happy customers and counting...
Overall, over 80% of customers chose to renew their subscriptions after the initial sign-up.
To try it out
For active job seekers
For those who are passive looking
Cancel anytime
Frequently Asked Questions
- We prioritize job seekers as our customers, unlike bigger job sites, by charging a small fee to provide them with curated access to the best companies and up-to-date jobs. This focus allows us to deliver a more personalized and effective job search experience.
- We've got over 200,000 jobs from 15,000+ vetted companies. No fake or sleazy jobs here!
- We aggregate jobs from 15,000+ companies' career pages, so you can be sure that you're getting the most up-to-date and relevant jobs.
- We're the only job board *for* software engineers, *by* software engineers… in case you needed a reminder! We add thousands of new jobs daily and offer powerful search filters just for you. 🛠️
- Every single hour! We add 2,000-3,000 new jobs daily, so you'll always have fresh opportunities. 🚀
- Typically, job searches take 3-6 months. EchoJobs helps you spend more time applying and less time hunting. 🎯
- Check daily! We're always updating with new jobs. Set up job alerts for even quicker access. 📅
What Fellow Engineers Say