Applied Scientist - Computational Modeling, OMHS SCS
Amazon.com Services LLC - A57•2h ago
United StatesOnsiteFull-time
H-1B verified · 2310 LCAs
Top focus
Applied Scientist
- As an Applied Scientist on the Science SW team, you will be a versatile generalist who collaborates closely with other scientists and engineers teams to bring research to production across a broad portfolio of problems: from computer-vision perception platforms to building-wide optimization and orchestration. This role combines the scientific application of ML and applied mathematics with a strong product focus. It will be your job to frame ambiguous business problems as tractable scientific problems
- to implement novel ML systems, first-principles models, embedded systems prototypes
- performance optimizations in both prototype and production environments. Key job responsibilities
- Own the research and development of scientific and ML solutions across a broad range of problems spanning classical machine learning, statistical modeling, computer vision, optimization
- physics-informed / first-principles modeling in a production environment.
- Rapidly ramp on unfamiliar problem domains, frame ambiguous or open-ended business problems as tractable scientific problems, and prototype solutions end to end.
- 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 our deployment architecture. About the team Amazon is building next generation software, hardware
- processes that will run our global network of fulfillment centers that move millions of units of inventory
- ensure customers get what they want when promised. The Science Software team in the One MHS organization unlocks Material Handling Equipment (MHE) innovation through a multiplicity of disciplines within Artificial Intelligence (AI) and applied science, including Computer Vision (CV), Physics-Informed Neural Networks (PINNs), Optimization, Reinforcement Learning, classical Machine Learning, statistical modeling
- sensing-hardware prototyping. Rooted in first principles aligned experimentation, the team is dedicated to building self-optimizing fulfillment centers, developing the models that drive real-time, building-wide orchestration of MHE. We conduct experiments, develop models
- apply machine learning (ML) at scale to optimize throughput, flow, merge
- to improve operational performance across the fulfillment network.
- is in the process of obtaining, a Advanced degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field - Experience with programming languages such as Python, Java, C++ - Strong foundation in applied mathematics, statistics
- 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).
- PhD with a demonstrated track record of solving problems across more than one domain (e.g., computer vision, statistical modeling, optimization, signal processing, controls
- physical modeling). - Experience with computer vision and/or physics-informed and first-principles modeling. - Hands-on hardware prototyping experience (sensors, cameras, embedded / edge compute) and experience optimizing models for resource-constrained hardware. - Publications at peer-reviewed venues (e.g., CVPR, NeurIPS, ICML, ICLR
- 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
- 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
- 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
- parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, MA, Boston - 136,000.00 - 184,000.00 USD annually USA, MA, N.Reading - 136,000.00 - 184,000.00 USD annually USA, MA, Westboro - 136,000.00 - 184,000.00 USD annually
Required skills
PythonJavaPandasNumPyPyTorchTensorFlowscikit-learn