Senior Applied Scientist

Amazon is hiring a Senior Applied Scientist in San Francisco, United States. It pays $192k-$260k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
Pay on this posting starts 12% higher than the typical applied scientist posting on Level.
The posting mentions PyTorch, TensorFlow and Python among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Senior Applied Scientist to lead ML-driven perception pipelines and multi-modal sensor fusion for autonomous robotics.

pytorchtensorflowpythondeep-learningcomputer-vision

computer-visionmachine-learningperception-systemssensor-fusionrobotics

Amazon is seeking an exceptional Sr. Applied Scientist to lead the development of perception systems that harness the power of radar and thermal imaging — enabling robots to perceive and operate reliably in conditions where conventional vision alone falls short. In this role, you will develop ML-driven perception pipelines for non-traditional sensing modalities, pushing the boundaries of what robots can see, understand, and act upon in challenging real-world environments.

At Amazon, we leverage advanced robotics, machine learning, and artificial intelligence to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence.

As a Sr. Applied Scientist in Multi-Modal Perception, you will apply deep computer vision expertise alongside classical signal processing techniques for radar and thermal imaging — modalities that provide robustness in adverse conditions and sensing capability beyond the visible spectrum. You will develop ML-based methods to extract semantic and geometric information from radar point clouds, radar tensors, and thermal imagery, and fuse these with camera and depth data to build perception systems that are reliable, comprehensive, and ready for deployment at scale.

Your work will unlock new capabilities for our robots — enabling reliable detection, classification, and scene understanding in low-visibility conditions, cluttered environments, and scenarios where traditional RGB-based perception is insufficient. You will lead research that translates cutting-edge advances in deep learning and computer vision to these underexplored but high-impact sensing modalities.

Join us in building the next generation of multi-modal perception systems that will define the future of autonomous robotics at scale.

Key job responsibilities
- Lead the research, design, and development of ML-based perception pipelines for radar and thermal/infrared imaging modalities
- Develop deep learning models for object detection, classification, segmentation, and tracking using radar data (point clouds, range-Doppler maps, radar tensors) and thermal imagery
- Design and implement multi-modal fusion architectures that combine radar, thermal, camera, and depth data for robust, all-condition perception
- Develop novel representations and feature extraction methods tailored to the unique characteristics of radar and thermal sensors (sparsity, noise profiles, spectral properties)
- Build end-to-end perception systems — from raw sensor data processing and calibration to model training, evaluation, and real-time deployment
- Collaborate closely with Hardware, Navigation, Planning, and Controls teams to define sensor configurations and deliver integrated autonomy solutions
- Establish benchmarks, datasets, and evaluation frameworks for radar and thermal perception
- Mentor scientists and engineers; foster a culture of scientific rigor, innovation, and high-impact delivery
- Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents

A day in the life
- Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment
- Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations
- Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team
- Mentor team members while maintaining significant hands-on contribution to technical solutions

About the team
Our team is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.

Basic qualifications

- Experience programming in Java, C++, Python or related language
- PhD in computer science, electrical engineering, or related field
- 5+ years of hands-on experience in Computer Vision — including object detection, segmentation, tracking, or scene understanding
- Strong expertise in developing and deploying deep learning models for visual perception tasks
- Experience processing and applying ML-based approaches to radar data and/or thermal/infrared imagery
- Strong experience with deep learning frameworks (PyTorch, TensorFlow, or equivalent)
- Proven track record of delivering perception systems from research to production
- Strong publication record in top-tier computer vision, robotics, or ML venues

Preferred qualifications

- Experience in the autonomous driving industry, particularly in developing perception pipelines that leverage radar and/or thermal sensors for self-driving vehicles
- Hands-on experience with 4D imaging radar processing, radar signal processing, or radar-camera fusion in AV stacks
- Experience with thermal/LWIR camera systems for pedestrian detection, night-time perception, or adverse-weather sensing conditions
- Familiarity with radar-specific challenges: sparsity, multi-path reflections, clutter, Doppler ambiguity, and cross-modal calibration
- Experience with foundation models or large pre-trained representations adapted to non-RGB modalities (radar, thermal, SAR)
- Knowledge of sensor calibration, synchronization, and extrinsic/intrinsic parameter estimation across heterogeneous sensor suites
- Experience with sim-to-real transfer and synthetic data generation for radar and thermal modalities
- Familiarity with relevant datasets (nuScenes, Radiate, FLIR ADAS, DENSE, Astyx, RADDet, Boreas)
- Experience with real-time inference, model optimization (TensorRT, ONNX), and edge deployment
- Experience with ROS/ROS2 and real-time robotics middleware

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, SAN FRANCISCO - 192,200.00 - 260,000.00 USD annually
USA, CA, Sunnyvale - 192,200.00 - 260,000.00 USD annually

How we rate this

Senior Applied Scientist at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Applied Scientist is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $192k-$260k a year.
The role is based in US, CA, San Francisco.
The job was posted on May 20, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionMachine learningPerception SystemsSensor FusionRoboticsPyTorchTensorFlowPython

Also common in applied scientist jobs at this level

LLM Generative AI NLP Reinforcement learning Spark AWS

Pay

This job starts at: $192k
Typical applied scientist job: $172k

This posting starts 12% above the typical applied scientist job. See applied scientist jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where perception systems was part of your work. What did you do?
Tell me about a project where sensor fusion was part of your work. What did you do?
Tell me about a project where robotics was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Computer vision, Machine learning, Perception Systems, Sensor Fusion, and Robotics. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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