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Remote Applied Scientist Machine Learning Jobs in Gig Harbor, WA

Machine Learning Engineer

Bellevue, WA · On-site +1

$117K - $152K/yr

Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field * Strong ... Experience (academic or applied) with data pipelines, model training workflows, or large datasets

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

Senior Machine Learning Engineer

Seattle, WA · On-site +1

$186K - $300K/yr

Collaborate with Applied Scientists to translate bleeding-edge research (e.g., causal inference ... Employee divides their time between in-office and remote work. Access to an office location is ...

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

Senior Applied ML Engineer

Seattle, WA · Remote

$125K - $183K/yr

Bachelor's or Master's degree in Computer Science, Machine Learning, or related field. * 5+ years of experience designing and deploying applied ML systems at scale. * Experience with computer vision ...

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Remote Applied Scientist Machine Learning information

What does a remote applied scientist machine learning do?

A Remote Applied Scientist in Machine Learning develops and implements machine learning models to solve real-world problems, often from a location outside of a traditional office. Their work involves analyzing large datasets, designing algorithms, and collaborating with teams to deploy scalable solutions. They may also conduct experiments to improve model performance and stay up to date with the latest research in the field. Communication and documentation are important, as they often work with cross-functional teams remotely.

What are the key skills and qualifications needed to thrive as a remote applied scientist machine learning?

To thrive as a Remote Applied Scientist in Machine Learning, you need a strong background in mathematics, statistics, and computer science, often supported by an advanced degree and experience in ML algorithm development. Familiarity with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and tools for data processing and cloud computing is essential. Exceptional problem-solving ability, communication, and self-motivation are key soft skills for collaborating remotely and driving projects forward. These skills ensure you can independently design, implement, and communicate impactful machine learning solutions in a distributed work environment.

What can I expect in terms of collaboration and communication when working as a remote applied scientist machine learning?

As a Remote Applied Scientist in Machine Learning, you will frequently collaborate with cross-functional teams, including data engineers, product managers, and software developers. Communication typically takes place via video calls, chat platforms, and shared documentation, so strong written and verbal communication skills are essential. You may participate in regular virtual stand-ups, sprint planning, and code reviews to align on project goals and share progress. Remote work environments emphasize proactive communication and self-management to ensure seamless teamwork and project delivery.

Sr Applied Scientist, Amazon Supply Chain

Amazon

Seattle, WA • On-site, Remote

Full-time

Posted 28 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,122 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions.

Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.
We are looking for a Senior Applied Scientist to join our team that is building revolutionary enterprise applications leveraging machine learning, generative AI, and agentic AI to help millions of companies worldwide manage their day-to-day supply chain operations. Our mission is to accelerate our customers' businesses through intuitive, differentiated technology solutions that solve enduring supply chain challenges. We blend strategic vision with curiosity and Amazon's real-world operational experience to build opinionated, turnkey solutions that make the 'buy versus build' decision a no-brainer for our customers.
As a Senior Applied Scientist, you will design and develop state-of-the-art machine learning models and algorithms that power intelligent supply chain applications at global scale

You will work at the intersection of research and real-world product impact-translating scientific breakthroughs into production systems that serve millions of customers. We operate like a startup within AWS, offering you the opportunity to tackle unprecedented challenges while working with the latest technologies in deep learning, large language models, and optimization.
If you are passionate about pushing the boundaries of applied science, thrive in ambiguous problem spaces, and want to shape the future of supply chain intelligence while having the backing of AWS's extensive resources, we want to hear from you.
Key job responsibilities
Design, develop, and deploy novel machine learning models for demand forecasting, inventory optimization, anomaly detection, and supply chain decision-making.
Lead the development of GenAI and Agentic AI solutions that automate complex supply chain workflows and deliver intelligent, adaptive recommendations to customers.
Formulate real-world business problems as machine learning problems; define data requirements, model architectures, evaluation metrics, and experimentation frameworks.
Drive end-to-end applied science projects from ideation through experimentation, offline evaluation, A/B testing, and production deployment at scale.
Publish research findings in top-tier conferences (NeurIPS, ICML, KDD, AAAI) and file patents to advance Amazon's intellectual property.
Mentor and develop junior scientists; raise the technical bar for the science team through code reviews, design reviews, and knowledge sharing.
Collaborate closely with engineering, product management, and business stakeholders to translate scientific capabilities into customer-facing product features.
Influence the technical strategy and scientific roadmap for the organization; identify new areas of investment and emerging opportunities in AI/ML.
Establish and promote best practices for experimentation, model validation, and responsible AI development across the team.
About the team
The AWS Applied AI Solutions team builds enterprise applications that leverage Amazon's operational expertise to solve real-world supply chain challenges for millions of companies. We operate like a startup within AWS-moving fast, shipping iteratively using state-of-the-art AI technologies

We invest in your growth through mentorship from senior scientists, conference publication support, and internal science reading groups. Amazon values diverse experiences-even if you don't meet all preferred qualifications, we encourage you to apply. If your career hasn't followed a traditional path, don't let that stop you.
ABOUT AWS:
Diverse Experiences
Amazon 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.
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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
Mentorship and 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.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US