Applied Scientist , Fauna
Company websiteamazon.com (Amazon, opens in new tab)
Base salary $172,400 to $223,400
Employer-published annual base salary, USD. Advertised base range in New York, NY
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationNew York, NY
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
We are seeking an Applied Scientist to develop and optimize Visual Inertial Odometry (VIO) and sensor fusion systems for our intelligent robots. In this role, you will design, implement, and deploy state estimation and tracking algorithms that enable robots to understand their position and motion in real time, even in challenging and dynamic environments.
You will own the full pipeline from algorithm development through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the boundaries of classical perception methods, combining learned representations with geometric techniques to achieve robust, real-time performance.
This is a deeply hands-on role. You will work directly with sensors, hardware, and real-world data, while prototyping, testing, and iterating in physical environments. The ideal candidate has strong foundations in VIO and sensor fusion, practical experience optimizing algorithms for embedded platforms, and familiarity with how modern deep learning is transforming perception.
Key job responsibilities
- Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout
- 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 (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches
- Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems
- Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack
- Lead technical projects from research prototyping through production deployment
Basic Qualifications
- 3+ years of building models for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Hands-on experience developing and deploying Visual Inertial Odometry or visual-inertial SLAM systems
- Strong understanding of multi-sensor fusion (cameras, IMUs, odometry) and state estimation (EKF, factor graphs)
- Experience optimizing perception algorithms for embedded or resource-constrained hardware
- Demonstrated hands-on experience with real sensor data, calibration, and physical robot platforms
- Familiarity with modern ML approaches to perception (learned feature extraction, depth prediction, end-to-end odometry)
Preferred Qualifications
- Experience using Unix/Linux
- Experience in professional software development
- Publication record at major robotics or computer vision conferences (e.g., ICRA, IROS, RSS, CVPR, ECCV)
- Experience with real-time systems programming and performance profiling on ARM/GPU platforms
- Experience with state estimation on legged robots
- Experience with stereo vision systems, camera-IMU calibration, time synchronization, and sensor characterization
- Track record of shipping VIO or SLAM systems to production on physical robots at scale
- Experience with NVIDIA Jetson, Qualcomm RB5, or similar embedded AI platforms
- Familiarity with ROS/ROS2
- Experience integrating learned perception modules (e.g., neural depth, feature matching networks) into geometric estimation pipelines
- History of technical leadership and cross-functional collaboration
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, NY, New York - 172,400.00 - 223,400.00 USD annually
Source: Amazon · View original posting (opens in new tab)
Pay in context
This role's base floor ($172,400) is above 42% of the 464 Data & ML roles in New York listed on this site; 15 others list the same floor. Their median floor is $175,300; the middle half runs from $150,000 to $200,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingApplied Scientist , Fauna$172,400 to $223,400
Data Center Cluster Operations Leader, DCC Communities$170K to $265K
Data Center Cluster Operations Leader, AWS Data Centers$170K to $265K
Manager, Data Engineering, GMT Global Operations Engineering and Support$170K to $230K
Sr. Workday Application Analyst, Finance & Adaptive, Grocery Tech Business Operations & Program Management$170K to $230K
IT App Analyst III - AMZ10322420$170K to $230K
Sr. Manager, Data and Insights, US Prime & Marketing Technology$170,600 to $230,800
Chart as a table
| Role | Published base |
|---|---|
| Applied Scientist , Fauna (this listing) | $172,400 - $223,400 |
| Data Center Cluster Operations Leader, DCC Communities | $170K - $265K |
| Data Center Cluster Operations Leader, AWS Data Centers | $170K - $265K |
| Manager, Data Engineering, GMT Global Operations Engineering and Support | $170K - $230K |
| Sr. Workday Application Analyst, Finance & Adaptive, Grocery Tech Business Operations & Program Management | $170K - $230K |
| IT App Analyst III - AMZ10322420 | $170K - $230K |
| Sr. Manager, Data and Insights, US Prime & Marketing Technology | $170,600 - $230,800 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-11-05
Where this pay comes from
Location as the employer wrote it: US, NY, New York
USA, NY, New York - 172,400.00 - 223,400.00 USD annually
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
