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Autonomous Navigation Jobs (NOW HIRING)

Diligent Robotics

Sr. ML Engineer, Autonomous Navigation

$107K - $146K/yr

As a Sr. ML Engineer, Autonomous Navigation, you will develop learning-based navigation models that enable Moxi to move naturally and safely around people, beds, wheelchairs, and equipment. You'll ...

Talentry, LLC

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Machine Learning Guru (Autonomous Navigation)**

Houston, TX · Remote

$200K - $300K/yr

Work on cutting-edge autonomous navigation technology. * Opportunity to contribute to world-first innovations. * Vibrant and fast-paced work environment. * Exposure to cross-team projects and ...

Hyphen Connect Limited

SLAM Architect (Robotics)

Seattle, WA · On-site

$63 - $86.25/hr

We are seeking a skilled SLAM Architect to drive the development of advanced autonomous navigation systems. This role involves creating innovative solutions for Visual-Inertial SLAM, dynamic obstacle ...

Hyphen Connect Limited

SLAM Architect (Robotics)

Boston, MA · On-site

$60 - $82.25/hr

We are seeking a skilled SLAM Architect to drive the development of advanced autonomous navigation systems. This role involves creating innovative solutions for Visual-Inertial SLAM, dynamic obstacle ...

Hyphen Connect Limited

SLAM Architect (Robotics)

Seattle, WA · On-site

$63 - $86.25/hr

We are seeking a skilled SLAM Architect to drive the development of advanced autonomous navigation systems. This role involves creating innovative solutions for Visual-Inertial SLAM, dynamic obstacle ...

Lunar Outpost

Autonomy Engineer

Arvada, CO

Designand develop of decentralized navigation and decision-making algorithms for lunar roversand orbital assets. * Develop and implement robust software capable of enabling autonomous operations in ...

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Autonomous Navigation information

What is autonomous navigation?

Autonomous navigation refers to the technology and processes that enable vehicles or robots to move through an environment and reach a destination without human intervention. This involves using sensors, artificial intelligence, and algorithms to perceive the surroundings, plan paths, and avoid obstacles. Autonomous navigation is widely used in self-driving cars, drones, robotic vacuum cleaners, and industrial robots. The technology continues to evolve rapidly, enhancing safety, efficiency, and versatility across various industries.

What are the key skills and qualifications needed to thrive in Autonomous Navigation roles, and why are they important?

To excel in Autonomous Navigation, you need a strong background in robotics, computer vision, sensor fusion, and algorithm development, typically supported by a degree in robotics, computer science, or a related engineering field. Familiarity with tools such as ROS (Robot Operating System), SLAM algorithms, LIDAR, and programming languages like Python or C++ is essential. Critical soft skills include problem-solving, teamwork, and adaptability to rapidly changing technologies. These skills and qualities are crucial for developing reliable navigation systems that can safely and efficiently operate in complex, real-world environments.

What is the difference between Autonomous Navigation vs Path Planning Engineer?

AspectAutonomous NavigationPath Planning Engineer
Required CredentialsDegree in Robotics, Computer Science, or related fields; experience with sensors and algorithmsSimilar credentials; focus on algorithms and robotics
Work EnvironmentRobotics labs, field testing, autonomous vehicle developmentRobotics teams, simulation environments, vehicle systems
Industry UsageAutonomous vehicles, drones, robotics systemsAutonomous vehicles, robotics companies, research institutions
Comparison FocusOverall navigation capabilities of autonomous systemsSpecific algorithms for generating feasible paths

Autonomous Navigation involves the entire process of enabling a robot or vehicle to move safely and efficiently in an environment, integrating perception, localization, and decision-making. Path Planning Engineer specializes in designing algorithms that determine the optimal route within the navigation system. While both roles require similar skills and work in related environments, Autonomous Navigation covers the broader system, whereas Path Planning focuses specifically on route generation.

How does an Autonomous Navigation engineer typically collaborate with cross-functional teams during a project?

As an Autonomous Navigation engineer, you will frequently work alongside robotics hardware teams, software developers, and data scientists to integrate navigation algorithms into real-world systems. Collaboration often involves regular meetings to align on system requirements, troubleshooting integration issues, and field-testing prototypes. Effective communication and a willingness to iterate quickly are key, as navigation performance depends on close coordination between sensing, perception, and control subsystems. This collaborative environment provides valuable learning opportunities and exposure to various aspects of robotics development.
Sr. ML Engineer, Autonomous Navigation

Sr. ML Engineer, Autonomous Navigation

Diligent Robotics

Remote

$107K - $146K/yr

Full-time

Posted 2 days ago

Job description

What we're doing isn't easy, but nothing worth doing ever is.
We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven team as we build out current and future generations of robots.
As a Sr. ML Engineer, Autonomous Navigation, you will develop learning-based navigation models that enable Moxi to move naturally and safely around people, beds, wheelchairs, and equipment. You'll train policies using fleet data (imitation learning) and refine behavior with simulation and RL. Your work will directly impact delivery speed, reduced hesitation/deadlocks, and fewer interventions in real hospital deployments.
Responsibilities
  • Develop learning-based navigation models that predict safe, smooth trajectories from sensor inputs and/or perception representations.
  • Build imitation learning pipelines from fleet logs (trajectory extraction, filtering, scenario balancing, evaluation).
  • Implement simulation-based refinement (RL, reward shaping, domain randomization) to improve robustness.
  • Define navigation success metrics aligned to product outcomes.
  • Collaborate with the AI Platform team to integrate learned policies behavior/safety systems and validate on-robot.
  • Build regression tests and scenario replay suites for challenging scenarios.
  • Analyze field behavior, identify failure modes, and close the loop through data curation and retraining.
Basic Qualifications
  • Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD a plus).
  • 5+ years of experience in ML for robotics and/or autonomous vehicles.
  • Experience with Vision-Language-Action (VLA) models, behavior cloning, and/or transformer/diffusion policies for robotic control.
  • Strong proficiency in PyTorch and experience with sequence models / policy learning.
  • Experience with imitation learning and/or reinforcement learning in robotics or autonomy contexts.
Preferred Qualifications
  • Experience with socially-aware navigation, dynamic obstacle avoidance.
  • Experience with RL at scale (simulation rollouts, distributed training, stability/debugging).
  • Familiarity with ROS navigation stacks and safety constraints for mobile robots.
  • Experience building eval harnesses (offline replay, scenario libraries).

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