Senior Tomographic Algorithm Engineer to develop and refine algorithms for tomographic imaging, transitioning research-grade code into robust market-ready products.
Responsibilities
Develop and refine algorithms for tomographic imaging
Transition research-grade code into robust market-ready products
Implement POCA (Point of Approach) and ASR (Advanced Scattering) methodologies
Resolve hit-ambiguity in high-flux environments
Validate and test models against real physical objects
Develops new, innovative solutions to problems plaguing the seismic industry using knowledge of signal processing, wave propagation, and numerical optimization to develop and test high-end algorithms, sequences, or programs.
Compensation
Performance based monthly bonus averaging at 10-15% at entry level (contingent on financial & individual performance)
Responsibilities
Develop new, innovative solutions to problems plaguing the seismic industry
Use knowledge of signal processing, wave propagation, and numerical optimization to develop and test high-end algorithms, sequences, or programs
Participate in the validation of contributions with senior Research staff and Production staff by analyzing and evaluating processing and imaging results on synthetic and field data
Collaborate closely with Software Engineers on the development, deployment, and improvement of high-performance computing applications on GPU and CPU architectures
Present work and results to colleagues, clients, and externally at conferences and workshops
Lead the development of evaluation frameworks and data collection protocols for robotic capabilities, focusing on designing how to measure, stress-test, and improve robot behavior across real-world tasks.
Compensation
The base salary range for this position is listed below... 183,800.00 - 248,700.00 USD annually
Responsibilities
Design and implement evaluation frameworks to measure robot capabilities across structured tasks, edge cases, and real-world scenarios
Develop task definitions, success criteria, and benchmarking methodologies that enable consistent and reproducible evaluation of policies
Create and refine data collection protocols that generate high-quality, task-relevant datasets aligned with model development needs
Build and iterate on teleoperation workflows and operator interfaces to support efficient, reliable, and scalable data collection
Analyze evaluation results and collected data to identify performance gaps, failure modes, and opportunities for targeted data collection
This internship focuses on rigorous benchmarking of machine learning and optimization methods for inverse design and optimization. You will develop a reproducible benchmarking framework for comparing an existing engineering design workflow with selected academic and open-source methods across representative inverse design and optimization problems.
Responsibilities
Review relevant state-of-the-art research and available open-source implementations in inverse design, black-box optimization, reinforcement learning, and related methods as appropriate to the selected use cases.
Select a small set of technically meaningful baseline methods together with the supervising researchers.
Define representative engineering optimization problems with explicit design variables, objectives, constraints, parameter ranges, and simulation settings.
Establish matched experimental protocols covering initialization, random seeds, evaluation budgets, stopping criteria, and training or model-building costs.
Adapt and integrate baseline implementations with existing engineering simulation workflows.
Requirements
PhD currently pursuing or recently completed in Machine Learning, Computer Science, Electrical or Electronic Engineering, Applied Mathematics, or a related technical field
Quantitative Researcher for a new team focused on systematic corporate bond and credit derivatives strategies.
Locations (2)
Chicago, Illinois, United States
New York, New York, United States
Compensation
The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
Responsibilities
Independently conduct quantitative research, adopting a rigorous approach and using statistical and structural models
Contribute to all aspects of the research and production process, including implementation of fitting tools; data organization; generation of alphas, risk and TC models; P&L attribution, etc.
Proactively search for and prioritize new ideas and datasets for alpha potential
Contribute to continuous improvement of the investment process and infrastructure in collaboration with the portfolio managers, developers and traders on the team
Research Scientist Intern, Humanoid Control & Dexterous Manipulation (PhD)
Research Scientist Intern to help take novel ideas from inception to real hardware focusing on full body loco-manipulation and dexterous hands control policies. The role involves the full robotics stack including data collection, algorithm development, model training, and running algorithms on real robots.
Responsibilities
Independently design, develop, and analyze novel research ideas related to robotic simulation and control, with a focus on loco-manipulation and dexterous manipulation.
Deploy, test, and debug algorithms on real robots for sim-to-real transfer.
Collaborate with other researchers and engineers across multiple disciplines.
Communication of research agenda, progress and results to a diverse audience regularly.
Publish research results at top conferences and release code that contributes to the field of robotics.
Requirements
Ph.D. degree in robotics, computer graphics, computer vision, machine learning, or a related STEM field
Nice to have: developing interactive graphics applications
Design and implement machine learning models and algorithms that power advertiser-facing AI experiences, using generative AI to transform the advertising lifecycle.
Compensation
The base salary range for this position is listed below. ... 149,300.00 - 249,300.00 CAD annually
Responsibilities
Design and implement machine learning models and algorithms that power advertiser-facing AI experiences, ensuring scientific rigor from research through production deployment.
Conduct applied research to extend or invent new approaches for complex advertising problems where no textbook solutions exist, working backwards from advertiser needs.
Collaborate with engineering, product, and science teams to integrate your solutions directly into large-scale production systems serving millions of advertisers.
Analyze experimental results and system performance to identify improvement opportunities, making informed tradeoffs between model complexity, latency, and business impact.
Mentor other scientists, provide peer feedback on research procedures and results, and contribute to the team's scientific roadmap and technical direction.
Building advanced machine learning systems using GenAI/LLM/VLM technology to manage the safety of millions of transactions and prevent eCommerce fraud through automation.
Compensation
The base salary range for this position is listed below... 142,800.00 - 193,200.00 USD annually
Responsibilities
Innovate with the latest GenAI/LLM/VLM technology to build highly automated solutions for efficient risk evaluation and automated operations
Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to create impactful business value
Learn, explore and experiment with the latest machine learning advancements to create the best customer experience
Build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation
Provide clear and compelling reports for solutions and contribute to ongoing innovation and knowledge-sharing
Develop and optimize Visual Inertial Odometry and sensor fusion systems for Amazon’s intelligent robots.
Compensation
USA, NY, New York - 172,400.00 - 223,400.00 USD annually
Responsibilities
Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms
Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking
Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU-accelerated edge devices) under strict latency and power constraints
Apply modern ML-based perception techniques to complement and improve classical geometric approaches
Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems
Requirements
Nice to have: Unix/Linux
Nice to have: professional software development
Nice to have: publications at major robotics or computer vision conferences
Nice to have: real-time systems programming
Nice to have: performance profiling on ARM/GPU platforms
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, WA, Seattle - 142,800.00 - 193,200.00 USD annually
Responsibilities
Own KPIs that measure theft/fraud management performance and efficiencies.
Detect and automate theft, fraud MOs
Detect organized crime rings and bad actor clusters
Perform end to end evaluation of operational defects, system gaps, and scaling challenges (both system and operational).
Contribute to the overall fraud management and product development strategies.
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)
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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