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Humanoid Jobs in Ohio (NOW HIRING)

$90 - $140/hr

Your mission & challenges We are growing our legged-robotics capability on NEURA's humanoid (4NE-1) and quadruped platforms. This role spans both core layers of the legged control stack: trajectory ...

$140 - $180/hr

NEURA's humanoid robot is a deeply complex cyber-physical system: distributed computing, high-density power electronics, a body-area sensor network, real-time actuation control, and a cognitive AI ...

Showing results 21-25

Humanoid information

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How much do humanoid jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for humanoid in Ohio is $23.19, according to ZipRecruiter salary data. Most workers in this role earn between $16.68 and $31.54 per hour, depending on experience, location, and employer.

What is a humanoid?

Humanoids are robots or artificial beings designed to resemble and mimic human form and behavior. They typically have a torso, head, two arms, and two legs, and are developed to interact with their environment and people in a human-like way. Humanoids are used in research, healthcare, customer service, and entertainment to perform tasks that require human-like movement or interaction. Advances in artificial intelligence and robotics have made humanoids increasingly capable of understanding speech, recognizing faces, and performing complex tasks safely alongside humans.

What are the key skills and qualifications needed to thrive as a humanoid?

I'm sorry, but 'Humanoid' is not a recognized real-world professional occupation, so I cannot provide an answer for this job title.

What are some typical challenges faced by humanoid robot engineers when working on human-robot interaction features?

Humanoid Robot Engineers often encounter challenges related to developing intuitive and safe human-robot interaction features. These include ensuring that the robot can interpret human gestures, speech, and emotions accurately while maintaining user safety in dynamic environments. Additionally, integrating sensory feedback, real-time processing, and adaptive learning into compact hardware can be complex. Collaborating closely with software developers, mechanical engineers, and UX designers is essential to address these challenges and deliver effective solutions.

What is the difference between Humanoid vs Robot Technician?

AspectHumanoidRobot Technician
Required CredentialsTypically requires a degree in robotics, engineering, or related fieldsRequires technical training or certification in robotics or electronics
Work EnvironmentDesign, programming, and testing humanoid robots in labs or manufacturing facilitiesMaintains, repairs, and installs various robots in industrial or commercial settings
Industry UsageUsed in research, entertainment, and advanced manufacturingCommonly employed in factories, automation plants, and service industries

Humanoids are specialized robots designed to mimic human appearance and behavior, often requiring advanced programming and design skills. Robot technicians focus on maintaining and repairing various types of robots, including humanoids, in industrial environments. While both roles involve robotics, humanoids are more involved in development and research, whereas robot technicians handle operational maintenance.

What are popular job titles related to Humanoid jobs in Ohio?

For Humanoid jobs in Ohio, the most frequently searched job titles are:

Infographic showing various Humanoid job openings in Ohio as of August 2026, with employment types broken down into 2% Internship, 87% Full Time, 6% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $48,232 per year, or $23.2 per hour.

Locomotion & Whole-Body Control Engineer (human)

NEURA Robotics

On-site

$90 - $140/hr

Other

Posted 15 days ago


Job description

Your mission & challenges

We are growing our legged-robotics capability on NEURA's humanoid (4NE-1) and quadruped platforms. This role spans both core layers of the legged control stack: trajectory optimization and MPC for kino-dynamic motion generation, and QP-based instantaneous whole-body control for executing those motions on real hardware at 1 kHz.

The work is focused on contact-rich dynamics, real-time optimization, and reliable execution on physical robots. You will collaborate closely with state estimation, simulation, low-level control, and hardware stakeholders, and with the application teams whose tasks ultimately depend on robust, predictable locomotion and whole-body behaviour.

  • Whole-body motion generation and control for floating-base legged platforms — locomotion, balance, contact transitions, and loco-manipulation (walking while manipulating).
  • Trajectory optimization and model-predictive control pipelines over robot state, contact schedules, ground reaction forces, centroidal momentum, and joint trajectories — using reduced-order locomotion models such as LIPM, SRBD, and centroidal dynamics.
  • QP-based task-space inverse dynamics for executing instantaneous whole-body control from MPC and trajectory-optimization references at 1 kHz on the real robot.
  • Whole-body modelling for the platform: floating-base rigid-body dynamics from URDF / MJCF, joint configuration, FK / IK, Jacobians, and mass / Coriolis / gravity computation.
  • Constraint formulation across the MPC and QP layers — contact, friction, torque, joint, kinematic, and stability constraints — with task-hierarchy design appropriate to the platform.
  • Solver performance work across both layers: warm-starting, numerical conditioning, constraint handling, and real-time reliability at 500 Hz – 1 kHz.
  • Deployment, tuning, and debugging of MPC, trajectory optimization, IK, and inverse dynamics pipelines on physical robots — including platform-specific contact-model calibration and validation against real robot data.
  • High-performance C++ for real-time execution; Python tooling for analysis, prototyping, and debugging.
What we can look forward to
  • MSc or PhD in robotics, controls, mechanical or electrical engineering, computer science, or a related field.
  • 4+ years of hands‑on experience developing trajectory optimization, MPC for locomotion, and / or whole-body control on physical robots.
  • Strong foundation in floating‑base articulated rigid‑body dynamics and contact modelling.
  • Strong working knowledge of reduced‑order locomotion models (LIPM, SRBD, centroidal dynamics, or equivalents) and their use inside MPC.
  • Strong foundation in optimal control, constrained numerical optimization, and model‑predictive control for legged robots.
  • Hands‑on experience with whole‑body QP / TSID frameworks on real robot data — including QP / DDP solver internals.
  • Hands‑on experience deploying real‑time control / MPC / WBC pipelines at 500 Hz – 1 kHz on hardware.
  • Strong C++ for real‑time robotics software; Python for analysis, tooling, prototyping, and debugging.
  • Practical understanding of how contact dynamics, actuator limits, latency, state‑estimation error, solver failure modes, and model mismatch behave on real hardware.
  • A collaborative working style: shared design, constructive code review, proactive communication, and reliable coordination across control, estimation, simulation, low‑level control, and hardware disciplines. Strong teamwork is essential for this role.
Nice to Have
  • Hands‑on experience on humanoids, quadrupeds, or other high-DOF legged robots.
  • Familiarity with Pinocchio, MuJoCo, Crocoddyl, IPOPT, TSID, OCS2, or similar open-source tools.
  • Hierarchical QP, weighted QP, task prioritization, contact force optimization, or operational-space control.
  • Contact planning, gait optimization, balance recovery; CPG-based or hybrid CPG / MPC controllers.
  • Multi-contact WBC: foot contact, bimanual grasping, or base‑arm coordination.
  • Contact-consistent dynamics and impact‑aware control transitions.
  • Experience with torque‑controlled robots and high‑bandwidth electric actuation.
  • Publications at RSS, ICRA, IROS, or CoRL in legged locomotion or whole-body control.
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