Robot Operating System (ros)

Robot Operating System (ros) Developer Jobs

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Today

Senior Robotics Systems Software Engineer

Cyngn Mountain View, CA

Mountain View, CA

Today

$180k - $200k/yr Full time Senior Autonomous Driving Engineer

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Job Description

Cyngn’s Autonomy team is building and deploying software for autonomous industrial vehicles, and this role focuses on end-to-end engineering across the autonomy stack. You will help design, integrate, validate, and debug production-quality capabilities, from behavior and planning to controls, simulation, and field troubleshooting, working closely with engineers across perception, localization, vehicle infrastructure, hardware, QA, and operations.

This on-site position is based in Mountain View, CA, with a salary range of USD 180,000 - 200,000 per year. The Senior level requires 3+ years of hands-on robotics or autonomous systems software development experience.

What You’ll Do

Design, develop, test, and deploy software for autonomous industrial vehicles across behavior and decision-making, motion planning, controls, and related vehicle systems.
Write and maintain production-quality C++ and Python software for Cyngn’s autonomous vehicle platforms.
Develop and integrate algorithms for navigation, trajectory generation, vehicle control, obstacle handling, and autonomous behaviors.
Integrate autonomy software with sensors, drive-by-wire systems, vehicle hardware, and other onboard software components.
Bring up, validate, and debug software on real vehicles by tracing issues across autonomy modules, middleware, hardware interfaces, and vehicle behavior.
Create simulation scenarios and testing infrastructure, including metrics and regression tests to validate autonomy behavior before deployment.
Investigate field issues and edge cases by reproducing failures, identifying root causes, and implementing robust production solutions.
Support deployment and validation at customer facilities by translating real-world observations into improvements across the autonomy stack.
Collaborate closely with engineers in Planning, Controls, Perception, Localization, Vehicle Infrastructure, Hardware, QA, and Operations.
Contribute to architecture discussions, code reviews, technical design work, and continuous improvement for the autonomy software.

Required Qualifications

BS, MS, or PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a related technical field, or equivalent practical experience.
3+ years of hands-on experience developing software for robotics, autonomous vehicles, or other autonomous systems.
Strong proficiency in modern C++ and working proficiency in Python.
Hands-on experience developing, testing, and deploying software on real robotic systems.
Experience with ROS/ROS2 or comparable robotics middleware.
Working knowledge of core robotics concepts including coordinate frames, kinematics, state estimation, motion planning, feedback control, and sensor integration.
Strong systems-level understanding of how autonomy components interact with each other and with vehicle hardware.
Experience debugging complex robotic systems where failures may span multiple software modules or hardware interfaces.
Strong software engineering fundamentals, including algorithms, data structures, software architecture, testing, and code review.
Strong communication and problem-solving skills, with the ability to work effectively across multiple engineering disciplines.

Technologies

C++, Python, ROS, ROS2, Linux, Git, Docker, CMake

Benefits

Health benefits (Medical, Dental, Vision) through Aetna, Kaiser Permanente, and Guardian, with multiple plan tiers
Ancillary benefits including accident, critical illness, and hospital indemnity plans (Voya)
Company-paid basic life insurance, plus voluntary supplemental life for you and your dependents
Short-term and long-term disability insurance, fully paid by Cyngn
HSA and FSA (Health & Dependent Daycare)
Employee Assistance Program
1:1 Health Concierge
Company 401(k)
Commuter Benefits
Flexible PTO policy
Paid Parental Leave
Daily lunches for in-office employees and a fully-stocked kitchen with snacks and beverages

Bonus Qualifications

Technical depth in at least one area of robotics or autonomous systems, such as Behavior and decision-making; Motion planning; Vehicle or motion control
Experience developing autonomous vehicles, mobile robots, industrial robots, or similar systems
Experience with behavior trees, state machines, or other architectures for autonomous decision-making
Experience with search-based or sampling-based motion planning techniques such as A*, Hybrid A*, RRT, or related algorithms
Experience with feedback control, vehicle dynamics, trajectory tracking, MPC, or optimization-based control
Experience with simulation environments and automated autonomy testing
Experience integrating sensors, actuators, drive-by-wire systems, or embedded/real-time components
Experience developing tooling, metrics, and CI/CD infrastructure for robotic systems
Familiarity with Linux, Git, Docker, CMake, and modern software development workflows
Experience taking robotics functionality from prototype through validation and production deployment

First 90 Days

Build a working understanding of Cyngn’s autonomy architecture, simulation environment, vehicle platforms, development workflow, and deployment process.
Partner with engineers across autonomy, infrastructure, hardware, QA, and operations to trace representative vehicle behaviors, build working relationships, and identify high-value reliability, integration, and test-coverage risks.
Deliver one scoped production improvement, such as fixing a well-understood autonomy defect, adding a regression scenario, or improving diagnostic tooling, and validate it in simulation and, where appropriate, on a vehicle.
Propose a prioritized plan for addressing one or two larger cross-stack risks, including candidate success metrics, data sources, and how each metric will be measured.

By 6 Months

Complete a production-quality autonomy improvement spanning two or more subsystem boundaries and accepted into a release candidate and/or at production customer sites.
Establish baseline metrics and demonstrate early improvement, such as improved scenario pass rate, fewer interventions, reduced tracking error, or faster failure resolution.
Add reusable simulation scenarios, regression tests, diagnostics, or validation tools incorporated into team release-candidate testing.
Publish a technical design or process improvement reviewed and adopted by affected teams.

By 12 Months

Demonstrate sustained, measurable production improvement against the six-month baseline through broader deployment and fleet monitoring.
Own a significant autonomy capability from design through implementation, vehicle validation, deployment, and production monitoring.
Improve team effectiveness through documentation, code and design reviews, and reusable cross-stack debugging practices.
Demonstrate technical ownership through observable signals, such as serving as a reviewer for one or two repositories, leading triage for a class of field issues, or maintaining adopted runbooks and tools used by other engineers.

Interview Process

A real person will review your application.
A one-sided video interview to share background and cover basic questions.
A Recruiter touch point to review the process in more detail and answer questions.
A 45-minute interview with the hiring manager.
A full-loop process with 3-4 additional conversations covering technical and soft skills and culture fit.
A final onsite interview with the team.

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1d ago

Senior Machine Learning Engineer, Perception and Controls

Capstan Medical, Inc. West Menlo Park, CA

West Menlo Park, CA

1d ago

Full time Artificial Intelligence Computer Vision Data Analysis

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Job Description

Senior Machine Learning Engineer role supporting Capstan Medical’s robotics and controls team to deliver perception, pose estimation, and FDA-aligned validation for in-procedure medical guidance.

Responsibilities

Develop registration methods for intraprocedural imaging (fluoroscopy, echocardiography) to the heart valve robot.
Estimate the pose of catheters and implants from medical images.
Fuse image-based pose estimates with robot kinematics and additional sensing.
Quantify uncertainty for each estimate and improve estimate reliability.
Build data pipelines to capture, align, label, and version imaging and robot data for training and evaluation.
Use simulation and synthetic data when real clinical data is limited.
Fit and iterate device behavior models from data and collaborate with controls engineers to support control improvements.
Partner with clinical engineers and physicians to understand procedural imaging, outcomes, and acceptance criteria for accuracy.
Stay current with the literature, prototype promising approaches, and evaluate what works on Capstan’s datasets.
Deploy models onto the robot and meet real-time latency budgets.
Produce validation outputs, test datasets, and design documentation so learned components can pass FDA design controls.

Requirements

Education: MS in Computer Science, Electrical Engineering, Robotics, or a related field (PhD a plus).
Experience: 4+ years professional experience in computer vision or machine learning (classical or learned), including at least one system shipped to production on real-world data.
Experience working with scarce, noisy, or expensive data using approaches such as synthetic data, augmentation, self-supervision, or physics priors.
Experience applying ML to data from physical systems including robots, cameras, medical imaging, or sensors.
Ability to thrive in a fast-paced environment and own problems end-to-end.
Ability to work onsite 3–4 days per week, split flexibly between Santa Cruz, CA and West Menlo Park, CA offices, with at least 1 day per week in Santa Cruz.

Technologies

Python, PyTorch, C++
ROS, ROS2
ONNX, TensorRT
Kalman filters, factor graphs

Preferred Qualifications

Ultrasound or echocardiography experience (strongly preferred); fluoroscopy or X-ray experience also valuable (including 2D/3D registration or digitally reconstructed radiographs).
Experience tracking catheters, needles, surgical tools, or continuum robots in images.
Sensor fusion and state estimation, including Kalman filters or factor graphs.
System identification or learned dynamics for control, including residual models on top of physics.
Robotics software experience with ROS/ROS2 and on-device inference under latency constraints using ONNX and TensorRT.
Data platform and MLOps experience, including dataset versioning and experiment tracking.
Medical device or safety-critical background, including validating ML under FDA design controls.
Experience as an early ML engineer establishing tools, data practices, and evaluation others build on.
Publications at venues such as MICCAI, IPCAI, CVPR, ICRA, or IROS.

Skills

Real-World Machine Learning: shipping models to products that operate on real-world data with noise, drift, and edge cases.
Computer Vision: classical and learned vision, especially pose estimation, segmentation, tracking, and 2D/3D registration.
3D Geometry: rigid transforms, rotations, camera projection models, and calibration.
Programming: strong Python and PyTorch; comfortable reading and writing C++.
Data Engineering: building pipelines, datasets, and evaluation harnesses others can trust and reuse.
Research and Prototyping: turning promising ideas into working prototypes using recent papers as input.
Problem-Solving: operating with ambiguity by breaking down fuzzy goals into experiments.
Communication: explaining ML clearly to controls and clinical teams, documenting work effectively, and communicating when a model is good enough to trust.

Benefits

Outstanding benefits with medical, dental, and vision covered at 100% for you and your family, plus flex time off.
Fast-paced, collaborative environment focused on transformational cardiac healthcare technologies.
Work-hard, play-hard culture with office outings.

Workplace Type

Hybrid: Onsite 3–4 days per week across Santa Cruz and West Menlo Park, CA, with at least 1 day per week in Santa Cruz.

Reports To

Robotics & Controls Manager

AI Tools Notice

Capstan Medical may use artificial intelligence (AI) tools during parts of the hiring process (for example, reviewing applications, analyzing resumes, or assessing responses) to support recruitment teams by identifying potential inconsistencies or verification signals based on available information. These tools assist the team but do not replace human judgment. Final hiring decisions are made by humans.

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