Six Figure Work

Applied Scientist, Safe Control, Amazon Robotics, Compass

Amazon

Company websiteamazon.com (Amazon, opens in new tab)

Base salary $142,800  to $193,200

Employer-published annual base salary, USD. Advertised base range in Pasadena, CA

Apply (opens in new tab)

You apply on the employer's own site. Six Figure Work does not handle applications.

  • LocationPasadena, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (5 h ago) · observed since

About this job

We are seeking an Applied Scientist to join Compass. In this role, you will develop the core Control Barrier Function (CBF) algorithms that form the mathematical foundation of the Compass safety system. You will ensure they don't just work in theory but perform reliably on real robots under real-world conditions. You will push the boundaries of concepts central to CBFs: computing robust invariant sets, designing hybrid system formulations that handle contact transitions and mode switches, and developing backup-set approaches that leverage learned policies and multiple controllers. A key challenge of this role is bridging the gap between the mathematics of set invariance and the realities of hardware, including sensor noise, model uncertainty, computational budgets, and discrete state transitions. You will ensure that these algorithms are not only provably correct but also implementable within a safety-critical architecture that must be certified by a third-party. You will contribute directly to the next generation of CBF theory and its practical deployment across Amazon's diverse robot fleet.

Key job responsibilities

  • Develop and implement novel CBF algorithms that provide formal safety guarantees while minimizing conservatism to maximize the permissible operating envelope for each robot platform
  • Compute and refine invariant sets for complex, high-dimensional robotic systems, developing scalable methods that go beyond what existing analytical approaches can handle
  • Design formulations for hybrid dynamical systems, handling discrete mode transitions (e.g., contact/no-contact, stance/flight phases) with provable safety across switching boundaries
  • Address the theory-to-practice gap by developing methods that are robust to model uncertainty, sensor noise, actuation delays, and computational latency
  • Create reduced-order and full-order dynamics models with both white-box and black-box approach
  • Implement real-time optimization solvers that execute within the tight timing budgets of safety-critical control loops
  • Develop formal arguments and documentation sufficient to support third-party safety certification of algorithms
  • Validate algorithms through rigorous simulation and hardware experiments, characterizing failure modes and quantifying safety margins
  • Contribute to the theoretical foundations of CBFs through publications at top-tier controls and robotics venues
  • Collaborate with perception, planning, locomotion, and manipulation teams to accommodate the needs of upstream and downstream systems

A day in the life

Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:

1. Medical, Dental, and Vision Coverage

2. Maternity and Parental Leave Options

3. Paid Time Off (PTO)

4. 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

About the team

Work with the inventors of control barrier functions on a novel, universal approach to safe autonomy: one that scales across mobile robots, manipulators, mobile manipulators, and future robot platforms with dynamic stability. You'll push the boundary of safe performance by integrating safety with motion planning, RL, and foundation models, ensuring that safety is never a blocker to robot performance. Your work will underpin robots operating alongside people at Amazon's unprecendented scale.

Basic Qualifications

  • PhD, or Master's degree and 4+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
  • Deep expertise in Control Barrier Functions, including theoretical foundations and practical implementation
  • Strong mathematical background in dynamical systems theory, nonlinear control, and formal verification or reachability analysis
  • Proficiency in C++ and Python with experience implementing control algorithms for real-time systems
  • Publication record at relevant venues (e.g., CDC, ACC, ICRA, RSS, Automatica, TAC)

Preferred Qualifications

  • Experience in professional software development
  • Experience validating safety-critical algorithms on physical robotic hardware (not simulation-only)
  • Experience with hybrid systems theory and formulations that handle discrete transitions (e.g., contact events, mode switches)
  • Experience with robust or adaptive methods that account for parametric uncertainty or unmodeled dynamics
  • Knowledge of functional safety standards (IEC 61508, ISO 13849, ISO 26262) and experience preparing algorithms for third-party certification
  • Familiarity with real-time embedded systems and the constraints of deploying optimization-based controllers on safety-rated hardware
  • Experience formulating and solving optimization-based controllers (QPs, SOCPs) for real-time safety filtering

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.

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, PASADENA - 142,800.00 - 193,200.00 USD annually

Source: Amazon · View original posting (opens in new tab)

Pay in context

This role's base floor ($142,800) is above 13% of the 1,510 Data & ML roles in California listed on this site; 5 others list the same floor. Their median floor is $187,000; the middle half runs from $159,256 to $229,800.

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 range next to 6 other live Amazon roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Amazon roles with the nearest advertised base floor
RolePublished base
Applied Scientist, Safe Control, Amazon Robotics, Compass (this listing)$142,800 - $193,200
Design Technologist II, Elevated Shopping Experience$145,000 - $196,100
Senior Industrial Designer$145,200 - $196,500
Data Center Area Operations Manager$145,400 - $254,500
MDD DCO Cluster Manager$145,400 - $254,500
Data Center Area Operations Manager, Data Center Operations$145,400 - $254,500
Data Center Operations Cluster Manager$145,400 - $254,500

Same $100K to $400K scale as every card. All Amazon roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-10-12
Where this pay comes from

Location as the employer wrote it: US, CA, Pasadena

USA, CA, PASADENA - 142,800.00 - 193,200.00 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.