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State Estimation Jobs in Ohio (NOW HIRING)

NEURA Robotics

$77K - $95K/yr

Real-time state estimation: floating-base EKF/UKF implementation and tuning for pelvis pose, velocity, and foot contact state at RT loop rates; feeds downstream controllers and loco-manipulation ...

Stark Defence

This isn\u2019t a maintenance role: you\u2019re building the control and state-estimation foundation that every other system on the platform depends on, while growing a team of engineers who can own ...

Trimble, Inc.

Software Engineering Team Lead

Dayton, OH · On-site

$136K - $187K/yr

Bonus Points For: • Direct experience in New Product Introduction (NPI) workflows. • Technical background in Control and State Estimation Theory. • Proven track record in coaching, mentoring ...

Trimble

Software Engineering Team Lead

Dayton, OH · On-site

$136K - $187K/yr

Technical background in Control and State Estimation Theory. Proven track record in coaching, mentoring, and facilitating the development of engineering teams. Outstanding interpersonal ...

NEURA Robotics

$70K - $91K/yr

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 ...

NEURA Robotics

... state estimation). * SOM board bring-up and the Yocto BSP for each robot platform hardware revision: boot flow, kernel configuration, device trees, and driver work at the C/C++ boundary, with ...

NEURA Robotics

Nav2 or equivalent AMR navigation stack, docking cycles, optional PROFINET familiarity; for the Legged anchor: floating-base state estimation concepts, gait controller integration, fall detection ...

Michael Page USA

Estimator

Columbus, OH · On-site

$120K - $150K/yr

URGENTLY Seeking an Estimator with 5+ years in commercial estimating. Commercial experience would ... state or local law. MPI encourages applications from minorities, women, the disabled, protected ...

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State Estimation information

What is state estimation in the context of power systems?

State estimation is a process used in power systems to determine the most likely operating condition of an electrical grid based on available measurements and system models. It involves collecting data from various sensors and meters, processing this data to filter out errors or inconsistencies, and calculating the voltage magnitudes and phase angles at different nodes. This helps operators monitor the system's health, detect issues, and make informed decisions to maintain reliable and secure power delivery.

What are some common challenges faced by professionals working in state estimation roles in the power industry?

Professionals in state estimation often encounter challenges such as handling incomplete or noisy data from sensors, ensuring the accuracy and reliability of real-time system models, and integrating data from diverse sources across the power grid. Additionally, they must quickly identify and resolve discrepancies or anomalies in system status, which requires strong analytical skills and attention to detail. Collaboration with control room operators, engineers, and IT specialists is also essential to ensure seamless operation and data integrity.

What are the key skills and qualifications needed to thrive as a state estimation engineer, and why are they important?

To thrive as a State Estimation Engineer, you need a strong background in electrical engineering, power systems, and applied mathematics, often supported by a relevant degree. Familiarity with power system analysis tools (such as PSS®E or PowerWorld), SCADA systems, and programming languages like Python or MATLAB is typically required. Analytical thinking, problem-solving abilities, and effective communication help you interpret data and collaborate with cross-functional teams. These skills are vital for ensuring reliable power system monitoring, accurate grid operation, and swift response to system anomalies.

What is the difference between State Estimation vs Power System Operator?

AspectState EstimationPower System Operator
Primary RoleAnalyzes and computes the most accurate system state using measurementsManages and controls the power grid in real-time
Required CredentialsEngineering degree, certifications in power systems or controlEngineering or technical background, often with operational certifications
Work EnvironmentData analysis, software tools, control centersControl rooms, field operations, real-time decision making
Industry UsageElectrical utilities, grid managementElectric utilities, grid operators

While both roles are vital in power systems, State Estimation focuses on analyzing system data to determine the current grid state, whereas Power System Operators manage and control the grid in real-time to ensure stability and reliability.

What are popular job titles related to State Estimation jobs in Ohio?

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

What job categories do people searching State Estimation jobs in Ohio look for?

The top searched job categories for State Estimation jobs in Ohio are:

What cities in Ohio are hiring for State Estimation jobs?

Cities in Ohio with the most State Estimation job openings:

State Estimation jobs near you

Dynamics, System Identification & Estimation Engineer - PLA (human)

On-site

NEURA Robotics
See more jobs at NEURA Roboticsexternal

$77K - $95K/yr

Other

Posted 22 days ago

Job description

Your Mission & Challenges

  • Dynamic model accuracy ownership: defining model fidelity metrics and owning the gap between simulation behaviour and real-hardware behaviour across dynamic motion and contact-rich interactions

  • System identification on 4NE-1 hardware: motor constants, joint friction, transmission dynamics — excitation trajectory design, regressor fitting, observability analysis, iterative refinement against hardware data

  • Simulation model authoring and maintenance: MuJoCo and Isaac Sim models that match real-world behaviour under dynamic loading and contact; contact model parameterisation, actuator model calibration

  • Real-time state estimation: floating-base EKF/UKF implementation and tuning for pelvis pose, velocity, and foot contact state at RT loop rates; feeds downstream controllers and loco-manipulation policy inputs

  • Sim-to-real pipeline: parameter estimation loops, hardware-data-driven calibration, validation against motion capture or external reference systems — the continuous feedback loop between hardware campaigns and updated sim models

  • Failure mode ownership: debugging model-accuracy-driven failures — control instability from inaccurate dynamics, estimation drift or bias causing divergence, incorrect contact/force estimation leading to instability in dynamic interactions

  • Cross-team interface: supplying updated Pinocchio model parameters to the WBC and State Estimation Engineers in Core Robot Software; aligning on excitation trajectory designs with the Locomotion and RL/Control Engineers

What we can look forward to

  • MSc or PhD in Robotics, Mechanical Engineering, Electrical Engineering, or a related field with a strong foundation in dynamics, estimation, and control

  • 4+ years of experience developing state estimation or system identification solutions for real-time robotic systems — on real hardware, not simulation-only

  • System identification on physical robotic systems: excitation trajectory design, least-squares or maximum-likelihood regressor fitting, actuator and transmission parameter identification

  • State estimation implementation: EKF or UKF for floating-base pose, velocity, and contact state on a legged or mobile robot platform

  • Rigid body dynamics depth: contact modelling, actuator behaviour, and how model inaccuracies propagate to control instability — not just theoretical familiarity

  • Experience supporting control systems (MPC, WBC) or learned policies (RL) through hardware deployment — understanding how model quality gates policy transfer

  • C++ for production RT systems; Python for analysis, tooling, and calibration pipelines

Nice to Have

  • Humanoid or legged robot hands‑on experience — 4NE‑1 is a full-size humanoid; bipedal dynamics and contact complexity are directly relevant

  • Differentiable simulators for gradient‑based system identification (Brax, DiffTaichi, or comparable)

  • Sim-to-real transfer methodology: domain randomisation, adaptive calibration, residual physics modelling

  • Pinocchio for rigid‑body model computation and parameter sensitivity analysis

  • MuJoCo model authoring: MJCF contact parameters, actuator models, tendon dynamics

  • Factor graph‑based estimation (GTSAM, iSAM2) for tightly‑coupled IMU + kinematics fusion

  • Publications or open-source contributions in legged robot dynamics, system identification, or sim-to-real transfer

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