Applied Scientist II, Computational Modeling, OMHS SCS

Socket.dev; Boston (MA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon's fulfillment technology team seeks an Applied Scientist to translate research into scalable production systems across perception platforms and optimization tasks within the fulfillment network.

The role frames business problems as scientific challenges and builds ML systems, first-principles models, and edge deployments for real-world constraints, shaping the scientific direction of a growing organization.

Qualifications

• PhD in engineering, CS, ML, robotics, OR statistics or equivalent quantitative field.
• 1+ years of building ML models for business applications.
• Experience with Java, C++, Python or related language.
• Experience with PyTorch or TensorFlow and the scientific Python stack.

Responsibilities

• Design, develop, and deploy ML and scientific solutions spanning classical machine learning, statistical modeling, computer vision, optimization, and physics-informed modeling in production environments.
• Rapidly ramp on unfamiliar problem domains, frame ambiguous business problems as tractable scientific challenges, and prototype solutions end to end.
• Author or co-author research findings for internal or external peer-reviewed venues, and provide peer feedback on research procedures and results across teams.
• Prototype and evaluate sensing hardware and lightweight, edge-deployable models that run on commodity compute under real-world constraints.
• Collaborate across multiple science and engineering teams to integrate your solutions into deployment architecture, mentoring less experienced scientists along the way.

Skills

Machine learning

Statistics

Applied mathematics

ML model development

Education

PhD in engineering/quantitative field

Tools

PyTorch

TensorFlow

NumPy

SciPy

scikit-learn

pandas

Job description

Are you excited about applying machine learning and applied mathematics to real-world systems at massive scale? As an Applied Scientist on this newly formed team, you will collaborate closely with scientists and engineers to bring research into production across a broad portfolio of problems - from computer vision perception platforms to building-wide optimization and orchestration. You will frame ambiguous business problems as tractable scientific challenges and implement novel machine learning (ML) systems, first-principles models, embedded systems prototypes, and performance optimizations in both prototype and production environments. This is a ground-floor opportunity to shape the scientific direction of a new organization, where your contributions will directly influence how Amazon's fulfillment network operates and evolves.

Key job responsibilities

• Design, develop, and deploy ML and scientific solutions spanning classical machine learning, statistical modeling, computer vision, optimization, and physics-informed modeling in production environments.
• Rapidly ramp on unfamiliar problem domains, frame ambiguous business problems as tractable scientific challenges, and prototype solutions end to end.
• Author or co-author research findings for internal or external peer-reviewed venues, and provide peer feedback on research procedures and results across teams.
• Prototype and evaluate sensing hardware and lightweight, edge-deployable models that run on commodity compute under real-world constraints.
• Collaborate across multiple science and engineering teams to integrate your solutions into deployment architecture, mentoring less experienced scientists along the way.

A day in the life

You might start your morning reviewing experiment results from an overnight model training run, then shift into a design discussion with engineers on how to deploy a new computer vision model to edge hardware in a fulfillment center. After lunch, you could be prototyping a physics-informed optimization approach, writing up findings for a research paper, or pairing with a teammate to debug a tricky data pipeline. As part of a new and growing organization, you will have a direct hand in shaping team practices, scientific roadmaps, and the tools you use every day.

About the team

Our team sits within Amazon's fulfillment technology organization and applies a range of scientific disciplines - including computer vision, optimization, reinforcement learning, and statistical modeling - to improve how goods move through Amazon's global fulfillment network. We build the models and systems that drive real-time orchestration, optimizing throughput, flow, and operational performance at scale.

Basic Qualifications

• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
• 1+ years of building machine learning models for business application experience
• Experience programming in Java, C++, Python or related language
• Strong foundation in applied mathematics, statistics, and machine learning, with the versatility to work across multiple problem domains rather than a single specialization.
• Experience with popular deep learning frameworks (e.g., PyTorch, TensorFlow) and the scientific Python stack (e.g., NumPy, SciPy, scikit-learn, pandas).

Preferred Qualifications

• Experience in professional software development
• Publications at peer-reviewed venues (e.g., CVPR, NeurIPS, ICML, ICLR, or the leading venues in the candidate's home discipline).

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, MA, Boston - 142,800.00 - 193,200.00 USD annually

USA, MA, N.Reading - 142,800.00 - 193,200.00 USD annually