Brain Corp is a San Diego, California, USA-based AI company creating transformative core technology for the robotics industry. Our purpose is to create autonomous technology that helps the real world work better. Brain's robotic and AI solutions help retailers ensure that the right product is on the right shelf at the right price, in a clean environment. Through the BrainOS® Robotics Platform, which powers the largest global fleet of the Autonomous Mobile Robots (AMRs) in operation in commercial public spaces, Brain Corp delivers insightful and efficient automated solutions in both commercial floor cleaning and inventory management, empowering organizations and their employees to achieve more. Brain Corp currently powers more than 30,000 AMRs, representing the largest fleet of its kind in the world. Brain Corp is funded by the SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Named a top workplace by the San Diego Union Tribune and USA today in 2025, we make life-changing impacts through innovation, helping workers globally unlock thier abilties in orchestration with intelligent machinges.

Position Overview:

As a Staff Autonomy Engineer on our R&D team, you'll be one of the technical leaders setting direction for the AI that powers our robots. This is a hands-on technical leadership role: you'll architect systems that span perception, mapping, prediction, and planning; drive multi-quarter initiatives from research idea to fleet rollout; and raise the technical bar across the org. You'll work across team boundaries, partnering with engineering managers, product, and hardware to make decisions that ripple through the roadmap. You'll also be someone the team learns from — through code review, design review, mentorship, and the standards you set in your own work. We expect Staff engineers to be comfortable in deep technical waters across the modern autonomy stack: foundation models, learned policies, classical estimation and planning, and the production systems that knit them together.

Essential Job Functions:

Technical Leadership and Direction

• Set technical direction for major areas of the autonomy stack — perception, SLAM, prediction, planning, or the ML systems underneath them — and own the multi-quarter roadmaps that follow.
• Lead large, ambiguous projects end-to-end: scope the problem, pick the approach, drive execution across multiple engineers, and ship to the fleet.
• Make and defend the build-vs-borrow, learn-vs-classical, and depth-vs-breadth decisions that shape what the team works on for the next year.
• Partner with engineering managers, product, and hardware on staffing, sequencing, and risk; serve as a senior technical voice in cross-functional planning.
• Represent the team externally where useful — publications, conferences, recruiting, customer technical conversations.

Technical Excellence

• Architect and contribute to systems spanning learned perception (transformer-based detectors, VLMs for scene understanding), neural and classical SLAM (including Gaussian splatting and implicit representations where they earn their keep), behavior prediction, and motion planning.
• Drive adoption of modern learning approaches — imitation learning, diffusion policies, vision-language-action models, RL where appropriate — and integrate them with the classical components that still do real work in production.
• Build and improve the data engines and evaluation infrastructure that turn fleet logs into training data, regression suites, and shipped wins.
• Lead performance and deployment work on embedded compute: model optimization, quantization, distillation, and runtime engineering on GPU/accelerator hardware.
• Stay current with the literature and translate the parts that matter into our codebase — and recognize the larger fraction that doesn't.

Mentorship, Hiring, and Culture

• Mentor Senior and mid-level engineers; raise the bar through design review, code review, and the technical standards you model.
• Play a leading role in hiring: shape interview loops, calibrate decisions, close strong candidates, and own onboarding for new hires on the team.
• Champion engineering practices that compound — testing, observability, documentation, simulation infrastructure, developer tooling — and invest in the parts of the org that enable everyone else to ship faster.

Education and/or Work Experience Requirements:

• Master’s Degree. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field — or equivalent demonstrated experience.
• 7+ years of industry experience in embodied AI (robotics, self-driving, drones, or similar), with at least some of that time in a senior or lead capacity.
• Deep expertise in two or more of: machine learning, SLAM and state estimation, robotic perception, motion planning.
• Strong fluency in C++ and Python in a Linux environment.
• Demonstrated history of taking research ideas into production at meaningful scale.

Required Knowledge, Skills, Abilities, and Other Characteristics:

• Deep, hands-on expertise with PyTorch (and/or JAX), modern training infrastructure, and contemporary architectures (transformers, diffusion models, VLA/foundation models).
• Extensive experience designing robotic systems with ROS 2 (or comparable middleware) and modern simulation environments such as Isaac Sim, MuJoCo, or Gazebo.
• Strong record of shipping ML-driven features to production hardware — including the post-launch reality of monitoring, debugging weird failure modes, rollback, and on-call.
• Excellent systems and architectural judgment; able to defend a position and equally able to update it when the evidence changes.
• Modern software engineering fundamentals: CI/CD, code review culture, observability, and iterative delivery.
• Excellent written and verbal communication — design docs that set direction, talks that bring people along, and code that other engineers want to read.
• Bonus: experience with on-device acceleration (TensorRT, ONNX, custom CUDA kernels), large-scale data infra, or leading distributed teams.
• Bonus:Track record of research impact (publications at venues like CoRL, RSS, ICRA, NeurIPS, CVPR, ICML — or open-source equivalents) and of converting research into product.

Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Essential functions may require maintaining the physical condition necessary for sitting, walking or standing for periods of time; operating a computer and keyboard; talk and hear at normal room levels; using hands to finger, grasp, and feel; repetitive motion; close visual acuity to prepare and analyze data and figures; transcribing; viewing a computer terminal; extensive reading; lift, push, carry, or pull up to 20 pounds. 

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The noise level in the work environment is usually quiet to moderate. Employees are exposed to the typical office environment with computers, printers and telephones.

Salary Range:

The anticipated salary range for candidates who will work in San Diego, California is $169,525 to $205,215. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and length of experience within the job, type and length of experience within the industry, education, etc. Brain Corp is a multi-state employer and this salary range may not reflect positions that work in other states.

In addition to base pay, our competitive total rewards package consists of:

• A discretionary annual target bonus
• Stock options
• 401(k) plan with match (no waiting period and immediate vesting)
• Comprehensive suite of insurance benefits for employees (and their families) to include a variety of medical plan options (including an HSA with employer contribution), dental, vision, life and disability insurance, Employee Assistance Program (EAP), Legal/Identity support plans, pet insurance.
• Access to Flexible Spending Accounts (Medical and Dependent Care)
• Generous paid time off including flexible vacation, Paid Sick Leave, time off for volunteering in the community, 10 paid company holidays, and a winter company shutdown

Additional Perks include:

• Daily on-site lunch available in the San Diego office
• On-campus gym including pool and tennis courts in the San Diego office
• Opportunities to connect with colleagues including monthly game nights, hikes, wellness challenges, and community events 
• Internal continuous learning events 
• Opportunities to share your own interests and hobbies with the Company

Brain Corp is a San Diego, California, USA-based AI company creating transformative core technology for the robotics industry. Our purpose is to create autonomous technology that helps the real world work better. Brain's robotic and AI solutions help retailers ensure that the right product is on the right shelf at the right price, in a clean environment. Through the BrainOS® Robotics Platform, which powers the largest global fleet of the Autonomous Mobile Robots (AMRs) in operation in commercial public spaces, Brain Corp delivers insightful and efficient automated solutions in both commercial floor cleaning and inventory management, empowering organizations and their employees to achieve more. Brain Corp currently powers more than 30,000 AMRs, representing the largest fleet of its kind in the world. Brain Corp is funded by the SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Position Overview:

We are seeking a Staff Software Development Engineer in Test, Cloud Applications to lead the design and evolution of quality engineering architecture across our web applications, cloud services, mobile platforms, and data systems.

This role combines deep technical leadership with hands-on engineering, operating as a working lead responsible for both architectural quality initiatives and the mentorship and management of a team of SDETs. The Staff SDET will guide a small team of engineers while remaining actively involved in designing and building scalable automation frameworks and validation platforms.

The role focuses on building engineering-grade automation, quality platforms, and validation strategies that enable teams to deliver reliable systems at scale. The Staff SDET acts as a quality architect, partnering with engineering, platform, and product teams to embed validation directly into system design, CI/CD pipelines, and data workflows.

The ideal candidate combines strong software engineering skills in Python with deep expertise in distributed systems testing, cloud-native environments, mobile testing platforms, and data validation frameworks.

Essential Job Functions:

Automation Platform Development

• Design and implement scalable automation frameworks and validation platforms using Python
• Build reusable automation libraries and developer-facing tooling that enable teams to validate functionality earlier in the development cycle
• Architect automated validation strategies across:
• Modern web applications
• APIs and microservices
  Distributed cloud systems
• Mobile platforms
• Data pipelines and analytics platforms including ML outputs.
• Integrate automation frameworks into CI/CD pipelines to enable rapid feedback and high-confidence releases

Mobile Platform Validation

• Architect automated testing strategies for mobile applications across iOS and Android platforms
• Leverage cloud device platforms such as BrowserStack to enable scalable cross-device testing
• Integrate mobile automation into CI/CD pipelines to support validation across devices, operating systems, and configurations
• Define strategies for mobile UI testing, API validation, and end-to-end workflow testing

Cloud & Distributed Systems Validation

• Design validation strategies for cloud-native microservices architectures
• Enable automated testing for service interactions through contract testing, integration validation, and environment simulation
• Partner with infrastructure and DevOps teams to embed quality gates within deployment pipelines
• Drive improvements in system reliability, performance, and resilience testing

Data Platform Quality Engineering

• Architect automated validation for data pipelines, data transformations, and data platform services
• Establish frameworks to validate data integrity, schema evolution, lineage, and reproducibility
• Partner with Data Engineering teams to ensure quality is built into analytics and machine learning
• Partner with data science and ML Ops teams to ensure reproducibility, monitoring, and validation of ML models within production systems, including drift detection and model performance validation

Technical Leadership & Engineering Influence

• Act as a technical leader across engineering teams, influencing architecture and engineering practices to improve product quality and system reliability
• Collaborate with product management, development, and DevOps teams to align testing strategies with product goals
• Facilitate the adoption of AI/ML/LLM-enabled testing strategies where appropriate
• Contribute to system and design reviews to ensure new components are observable, testable, and resilient
• Shape the direction of the Quality Engineering discipline, driving adoption of modern testing approaches and tooling workflows

Working Lead & Team Leadership

• Serve as a working lead and manager for a team of SDETs, providing architectural guidance and mentorship
• Conduct performance reviews, support career development, and foster engineering excellence within the team
• Guide the team’s technical direction while remaining hands-on in framework design and automation architecture
• Coordinate quality engineering initiatives across projects to ensure alignment with organizational priorities

Data-Driven Quality Insights

• Establish metrics, dashboards, and observability strategies that provide real-time visibility into product health and release readiness
• Provide engineering leadership with data-driven insights into system reliability, defect trends, and risk areas
• Investigate system behaviors and diagnostic data to identify root causes and drive cross-team issue resolution
• Ensure traceability between requirements, implementation, and verification

Education and/or Work Experience Requirements: 

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience
• 7+ years of experience in software engineering or SDET roles working with complex distributed systems, with at least 3 years in a technical leadership role 
• Strong software development skills in Python, including building automation, tooling, or validation systems
• Demonstrated experience designing and implementing automation frameworks or validation platforms across multiple layers of the stack (UI, API, service, integration, and data)
• Strong experience validating web applications, APIs, and distributed microservices architectures
• Demonstrated ability to integrate automated validation strategies into CI/CD pipelines
• Strong understanding of modern software testing methodologies and quality engineering practices, including functional, integration, and system testing
• Experience implementing browser automation frameworks such as Playwright or Cypress
• Strong debugging and analytical skills, including the ability to investigate complex failures and support root cause analysis
• Demonstrated ability to mentor engineers and influence engineering practices within a team or product area
• Excellent communication, collaboration, and technical documentation skills
• Proven capability in utilizing AI/ML-assisted testing techniques to enhance coverage, diagnostics, and defect detection

Preferred Qualifications:

• Experience validating data platforms and data pipelines, including SQL-based systems, data warehouses, and ETL/ELT workflows
• Experience implementing contract testing or service-level validation strategies in distributed systems
• Experience building or improving quality dashboards, metrics, or reporting systems used to evaluate system health and release readiness
• Experience testing mobile applications and working with cross-device testing platforms

Things that make a difference:

• Master’s degree in Computer Science, CE, EE.
• Experience validating machine learning systems or ML-enabled applications, including model inference services, training data pipelines, or model output validation
• Experience with simulation-based testing environments, such as NVIDIA Isaac Sim or similar robotics simulation platforms
• Experience working in environments that combine cloud services, mobile applications, and data platforms
• Experience in mobile robotics or industrial automation is a plus
• Experience with common sensors used in robotics, including cameras (RGB and Depth), LIDARs, IMUs and Sonars is a plus

Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The physical activity of this position includes, kneeling; reaching; pushing; pulling; sitting, standing and walking for periods of time; using hands to finger and grasp; repetitive motion; talking and hearing. close visual acuity to prepare and analyze data and figures; transcribing; viewing a computer terminal; extensive reading; visual inspection involving small defects, small parts, and/or operation of machines; use of measurement devices; and/or assembly or fabrication parts at distances close to the eyes; push or pull up to 20 pounds.

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The noise level in the work environment is usually quiet to moderate. Employees are exposed to the typical office environment with computers, printers and telephones.

Salary Range:

The anticipated salary range for candidates who will work in San Diego, California is $133,500 to $155,000. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and length of experience within the job, type and length of experience within the industry, education, etc. Brain Corp is a multi-state employer and this salary range may not reflect positions that work in other states.

In addition to base pay, our competitive total rewards package consists of:

• A discretionary annual target bonus
• Stock options
• 401(k) plan with match (no waiting period and immediate vesting)
• Comprehensive suite of insurance benefits for employees (and their families) to include a variety of medical plan options (including an HSA with employer contribution), dental, vision, life and disability insurance, Employee Assistance Program (EAP), Legal/Identity support plans, pet insurance.
• Access to Flexible Spending Accounts (Medical and Dependent Care)
• Generous paid time off including flexible vacation, Paid Sick Leave, time off for volunteering in the community, 10 paid company holidays, and a winter company shutdown

Additional Perks include:

• Daily on-site lunch available in the San Diego office
• On-campus gym including pool and tennis courts in the San Diego office
• Opportunities to connect with colleagues including monthly game nights, hikes, wellness challenges, and community events 
• Internal continuous learning events 
• Opportunities to share your own interests and hobbies with the Company