Design, build, and deploy large-scale software systems that support ML-driven trading strategies, optimize inference pipelines, and integrate research models into production infrastructure.
Compensation
Base Salary Range
$200,000—$200,000 USD
Responsibilities
Design and build large-scale software systems for ML-driven trading
Develop and optimize inference pipelines for low latency and high throughput
Integrate research models into production infrastructure using Python, C++, and GPU environments
Investigate and resolve complex issues across research and production
Build tools and infrastructure for testing, deployment, monitoring, and iteration
Amazon.com’s Product Detail Page team is looking for a talented applied scientist to design and develop scalable multi-tiered shopping application features to enhance the online shopping experience worldwide.
Responsibilities
Develop next-generation optimization algorithms for Detail Page
Identify business opportunities and propose new features
Design and enforce company-wide technical standards
Support HPC and AI engineer responsible for operation, maintenance, and AI integration on high-performance computing platforms at Thales' Toulouse site.
Responsibilities
Follow daily HPC platform availability and performance
Assist users with HPC platform issues and optimization
Conduct studies on integration of innovative technologies
Design and integrate AI-based solutions
Optimize scientific application performance through audits and parallelization
Lead product strategy and roadmap for AI infrastructure stack, defining compiler, runtime, and framework integration features.
Responsibilities
Translate customer, engineering, and business requirements into detailed Product Requirements Documents (PRDs), technical specifications, and feature definitions.
Develop detailed product schedules, milestone plans, and release timelines while managing dependencies across multiple engineering organizations.
Define requirements for the software and AI model compilation toolchain.
Lead product partnerships and technical integrations with major machine learning frameworks and runtimes.
Define performance optimization roadmap for low-level operator libraries.
Requirements
Master of Science (M.Sc.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Doctor of Philosophy (Ph.D.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Nice to have: MBA
Nice to have: open-source AI infrastructure contributions
Build next-generation green intelligent computing infrastructure and drive breakthroughs in performance and energy efficiency of AI clusters through innovation.
Responsibilities
Build next-generation green intelligent computing infrastructure, driving continuous breakthroughs in performance and energy efficiency of AI clusters through innovative technology.
Participate in cutting-edge sustainable computing technology research and apply results to large-scale AI infrastructure scenarios.
Conduct cutting-edge research in sustainable computing and green AI, exploring energy efficiency optimization solutions for large-scale AI training and inference scenarios.
Design and build fine-grained energy consumption analysis systems to achieve precise energy monitoring, decomposition, and modeling from cluster, node, and device to task levels.
Develop dynamic frequency and voltage scaling (DVFS), resource management, and intelligent scheduling optimization algorithms for CPU/GPU/NPU resources to improve overall system energy efficiency.
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)
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