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Night Shift Robotics Engineer Localization Jobs in California

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Night Shift Robotics Engineer Localization information

What are some common challenges faced by night shift robotics engineer localization professionals, and how are they typically addressed?

Night Shift Robotics Engineer Localization professionals often encounter challenges such as troubleshooting localization errors in real-time with limited support staff available, maintaining high system uptime during off-peak hours, and ensuring seamless handovers with the day team. To address these, clear documentation practices, robust remote support protocols, and regular communication with cross-functional teams are essential. Additionally, night shift engineers often develop strong problem-solving skills and autonomy, which are highly valued for career advancement within robotics and automation fields.

What are the key skills and qualifications needed to thrive as a night shift robotics engineer localization, and why are they important?

A Night Shift Robotics Engineer in Localization requires strong proficiency in robotics systems, localization algorithms (such as SLAM), and a relevant engineering degree or equivalent experience. Familiarity with tools like ROS (Robot Operating System), sensor fusion frameworks, and programming languages like Python or C++ is commonly expected. Excellent problem-solving skills, attention to detail, and the ability to work independently during off-hours are crucial soft skills for this role. These competencies ensure reliable robot operation, effective troubleshooting, and smooth system performance during night shifts when immediate team support may be limited.

What does a night shift robotics engineer localization do?

A Night Shift Robotics Engineer specializing in Localization is responsible for ensuring that robots can accurately determine their position and orientation within a given environment during overnight hours. This involves working with sensors, mapping algorithms, and navigation systems to help robots move and operate autonomously. Night shifts are often required in facilities that operate 24/7, such as warehouses, manufacturing plants, or research labs. The role also includes monitoring robotic systems, troubleshooting localization issues, and performing maintenance or updates as needed during off-peak hours.

What is the difference between Night Shift Robotics Engineer Localization vs Night Shift Robotics Engineer Perception?

AspectNight Shift Robotics Engineer LocalizationNight Shift Robotics Engineer Perception
Required CredentialsBachelor's in Robotics, Electrical, or Mechanical Engineering; experience with localization algorithmsBachelor's in Robotics, Computer Vision, or related field; experience with perception systems
Work EnvironmentRobotics labs, manufacturing plants, or warehouse settings during night shiftsSimilar environments focusing on sensor data processing and object detection at night
Employer & Industry UsageAutonomous vehicle companies, logistics, and warehouse automationAutonomous vehicles, robotics research, and industrial automation

While both roles involve working with robotics during night shifts, Localization engineers focus on determining the robot's position within an environment, whereas Perception engineers work on interpreting sensor data to identify objects and surroundings. Both roles require similar technical backgrounds but differ in their core focus areas within robotics systems.

What cities in California are hiring for Night Shift Robotics Engineer Localization jobs? Cities in California with the most Night Shift Robotics Engineer Localization job openings:
Night Shift Robotics Engineer Localization jobs near you
Infographic showing various Night Shift Robotics Engineer Localization job openings in California as of July 2026, with employment types broken down into 92% Full Time, 4% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Research Robotics/Computer Vision Engineer

Skild AI

San Mateo, CA • On-site

Full-time

Re-posted 4 days ago

Job description

Position Overview

Skild AI, Inc. seeks a Research Robotics/Computer Vision Engineer in San Mateo, CA responsible for developing perceptive, intelligent, and adaptable robotic systems capable of learning and performing tasks with a focus on 3D computer vision and autonomous navigation. This includes designing perception pipelines, optimizing SLAM systems, and creating learning-based algorithms for robust robotic control in real-world environments. Specific duties include: (i) implementing perception on robots to enable safe exploration and navigation in real world environments in collaboration with the locomotion team; (ii) reconstructing an entire scene in 3D using monocular images, estimating camera poses, optimizing and streamlining 3D SLAM; (iii) developing a set of software tools for localization of a robot using only visual inputs; (iv) building robust software to enable life-long mapping on a robot via optimally merged pose-graphs; (v) visual servoing wrt objects detected/ tracked to control robot motion; (vi) researching novel techniques to detect and cater to glare during robotic mapping and navigation; (vii) building infrastructure and pipeline and collecting data to enable streaming of hand movements for training robot manipulation tasks such as pick and place; and (viii) maintaining a camera and 2D lidar based navigation stack, including fixing bugs, adding new customer feature requests, and ensuring successful deployments.

Responsibilities
  • (i) implementing perception on robots to enable safe exploration and navigation in real world environments in collaboration with the locomotion team
  • (ii) reconstructing an entire scene in 3D using monocular images, estimating camera poses, optimizing and streamlining 3D SLAM
  • (iii) developing a set of software tools for localization of a robot using only visual inputs
  • (iv) building robust software to enable life-long mapping on a robot via optimally merged pose-graphs
  • (v) visual servoing wrt objects detected/ tracked to control robot motion
  • (vi) researching novel techniques to detect and cater to glare during robotic mapping and navigation
  • (vii) building infrastructure and pipeline and collecting data to enable streaming of hand movements for training robot manipulation tasks such as pick and place
  • (viii) maintaining a camera and 2D lidar based navigation stack, including fixing bugs, adding new customer feature requests, and ensuring successful deployments.
Minimum Requirements
  • Must have a master's degree (or foreign equivalent) in Computer Vision, Robotics, or a directly related discipline and one (1) year of experience in Machine Learning or Data Science.
  • Must have any experience with or knowledge of each of the following: (i) reconstructing 3D scenes using monocular videos, meshes, pointclouds, Neural Radiance Fields, and Gaussian Splats; (ii) reconstructing rigid and articulated hand-held objects from videos, including inferring the time-varying hand configurations and relative poses of the objects; (iii) using generative computer vision, including diffusion models to guide reconstruction, or addressing occlusion and limited viewpoint variations in videos via data driven priors; (iv) optimizing attention-based models for perception used in autonomous navigation systems; (v) using Neural Architectural Search (NAS) to find better perception backbone architectures with higher accuracies and lower latencies; and (vi) cloud-based training in AWS, Google cloud, or Vetex AI and optimized data loading for cloud based distributed training for deep learning workloads (e.g. Pytorch dataloader, or sharding) with hardware-in-loop.
  • Experience can be concurrent.

Apply online at skild.ai/career.

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