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Motion Capture Acting Jobs (NOW HIRING)

10 Squared LLC

Senior Coach

Austin, TX · On-site

... Squared members, acting as the primary liaison between program members and the 10 Squared ... Experience using force plates, motion capture camera systems and other data collection devices

10 Squared LLC

Senior Coach

Austin, TX · On-site

$110K - $130K/yr

... Squared members, acting as the primary liaison between program members and the 10 Squared ... Experience using force plates, motion capture camera systems and other data collection devices

10 Squared LLC

Senior Coach (Injury Prevention)

Austin, TX · On-site

$120K - $150K/yr

... acting as a key liaison for a seamless experience. • Committing to ongoing education and training ... plates, motion capture camera systems and other data collection devices • Knowledge and ...

Apptronik

Staff Video Producer

Austin, TX · On-site

Direct on-set talent (engineers, executives, actors) and serve as a primary visual lead on set ... motion graphics partners for major campaigns. * Brand & Stills Photography (Secondary): Capture ...

Booster

Staff Video Producer

Austin, TX · On-site

Direct on-set talent (engineers, executives, actors) and serve as a primary visual lead on set ... motion graphics partners for major campaigns. * Brand & Stills Photography (Secondary): Capture ...

Booster

Direct on-set talent (engineers, executives, actors) and serve as a primary visual lead on set ... motion graphics partners for major campaigns. * Brand & Stills Photography (Secondary): Capture ...

Apptronik

Staff Video Producer

Austin, TX · On-site

Direct on-set talent (engineers, executives, actors) and serve as a primary visual lead on set ... motion graphics partners for major campaigns. * Brand & Stills Photography (Secondary): Capture ...

Just Hoop Inc

Sports Videographer

San Leandro, CA · On-site

$15.50 - $20/hr

Travels to various games, camps and events to capture shots and video footage. * May assist other ... motion graphics, color correction, and publishing. * Proven ability to be detail oriented, meet ...

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Motion Capture Acting information

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How much do motion capture acting jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for motion capture acting in the United States is $84.70, according to ZipRecruiter salary data. Most workers in this role earn between $79.81 and $86.06 per hour, depending on experience, location, and employer.

What is motion capture acting?

A Motion Capture Acting job involves performing movements and expressions that are recorded using motion capture technology to create realistic digital characters in films, video games, and animation. Actors wear specialized suits with markers or sensors that track their motions, which are then translated onto a computer-generated model. This requires physical expressiveness, body control, and sometimes voice acting. Motion capture actors often work closely with animators and directors to bring characters to life in a believable way.

What does a typical workday look like for a motion capture actor?

A day in Motion Capture Acting usually involves wearing specialized suits fitted with sensors, performing scripted actions or improvising movement sequences on a capture stage, and frequently collaborating with directors, animators, and other performers to achieve the desired character portrayal. Actors may work with minimal props or environmental cues, relying on their imagination and spatial awareness to interact with digital environments. Rehearsals are common, as is adapting to notes or feedback from the creative team to refine performance. Depending on the project, you may participate in both solo and ensemble capture sessions. The work environment is fast-paced, creative, and highly collaborative, offering opportunities to grow your skills and network within the film, gaming, and technology industries.

What are the key skills and qualifications needed to thrive in motion capture acting?

To excel in Motion Capture Acting, performers need advanced physical acting abilities, nuanced body awareness, and experience in movement-based disciplines such as dance, martial arts, or physical theater. Familiarity with motion capture suits, markers, facial rigs, and relevant digital capture systems is highly beneficial, although formal technical certifications are not always required. Strong collaboration skills, adaptability, and the ability to take direction help actors contribute effectively to creative teams and shifting production needs. These qualities are crucial for delivering believable, expressive performances that accurately translate into digital characters within film, video games, and other interactive media.

How do you become a motion capture actor?

To become a motion capture actor, you typically need acting experience, physical fitness, and the ability to perform in suits with markers or sensors. Training in movement, body awareness, and familiarity with motion capture technology can improve your chances, along with auditioning for mocap roles in video games, films, or VR projects.

How much money do motion capture actors make?

Motion capture actors' salaries vary based on experience, project scope, and union status, but they typically earn between $50,000 and $150,000 annually. Experienced performers working on major projects or with union membership can earn higher wages, often supplemented by per-session or project-based pay. Skills in acting, physicality, and familiarity with motion capture technology are important for higher earnings.
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What states have the most Motion Capture Acting jobs?

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Motion Capture Acting jobs near you
Infographic showing various Motion Capture Acting job openings in the United States as of September 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $176,166 per year, or $84.7 per hour.

Sr. Software Engineer - Data Collection

San Francisco, CA • On-site

Anvil Robotics
See more jobs at Anvil Roboticsexternal

$144K - $190K/yr

Full-time

Posted 23 days ago

Job description

You'll be the reason Anvil's data collection system goes from "the parts work" to "the whole thing works."
Anvil is building the platform layer for Physical AI: robotics hardware and software that is radically more accessible than legacy industrial solutions. We own and operate our own manufacturing, and in our first 12 months we built and shipped 200+ robots to customers in 60+ countries: NVIDIA's GEAR lab (the team behind GR00T), Physical Intelligence (the frontier lab behind pi0), Qualcomm, Toyota, Google, and the robot learning labs at Stanford, MIT, Columbia, CMU, and Georgia Tech. The researchers who define this field run their experiments on our hardware, and many of them bought it with their own money.
Devkits are the wedge, not the business. That volume has earned us a custom force sensing actuator partnership with major actuator OEMs, and the install base becomes both the distribution channel for our next generation robots and a platform for the data and software layers above them. The handheld data collection system is the front end of that strategy: the instrument that turns real world tasks into training data at scale.
Our handheld data collection system lets people capture high quality demonstration data for training robots to do real tasks, wherever the task actually happens, with no teleoperation rig and no motion capture stage required.
The situation you're walking into:
  • Anvil already has specialist engineers deep in each piece of this system: pose tracking, model training, SoC/chip integration, and industrial design. Each piece works, but nobody currently owns making them work together as one product a customer can actually pick up and use. That is the gap you would fill.

What you'll own:
  • Full technical ownership of pulling the handheld data collection software system together end to end.
  • Acting as the systems and product engineer across specialist teams, including pose tracking, model training, SoC/chip, and industrial design. You will not personally do their deep technical work, but you are the one who understands how it all needs to fit together, catches the gaps between teams, and makes the call on what integrates now versus later.
  • Building real infrastructure for parts of the system that do not have it yet, including turning the model team's scripts into something repeatable.

What the first 100 days look like:
  • By day 30: ramped on every major piece of the system, including pose tracking, app software, cloud pipeline, and the model team's current workflow, well enough to know where the real gaps are, not just the documented ones. Has personally used the device to collect data end to end at least once.
  • By day 60: has shipped a first concrete integration or reliability improvement that makes two previously disconnected pieces of the system actually work together better.
  • By day 100: is the person other engineers, including those in pose tracking, model training, SoC/chip, and industrial design, go to when something is not fitting together. Trusted with real technical judgment calls across team boundaries without formal authority over any of those teams.

Who you are:
  • You have done systems or product integration work for a robotic or perception based product before. You have been the person who made disparate technical pieces (hardware, perception, software, sometimes ML) work together into something a real user relied on. This matters more than depth in any single domain.
  • You have genuine, provable depth in at least one of the following, along with familiarity with several of the others:
    • Perception/robotics systems (SLAM, VIO, sensor fusion, mapping)
    • Embedded application development: you have gotten real applications built, deployed, and running reliably on constrained or embedded hardware
    • Cloud scale pose estimation or perception pipeline engineering: building systems that turn sensor data into trustworthy estimates reliably at scale
    • ML workflow, training, and deployment engineering
    • Physical AI and robot learning deployment, for example VLA style policies, getting a trained model to actually make a robot do something
  • You can operate as a team of one across teams you don't manage, building enough technical credibility in each domain to know when something's actually wrong versus just unfamiliar to you.
  • You default to shipping the smallest thing that actually closes an integration gap, rather than hacking something bespoke every time or overbuilding a general platform nobody's asked for yet.
  • Based in or willing to relocate to Taiwan, the USA, or Trinidad & Tobago. This is the same role and scope regardless of location.

Education & experience:
  • Master's degree in robotics, computer science, electrical engineering, or a related field - or a bachelor's with equivalent hands-on depth. A PhD is not required; this is a product integration role, not a research role.
  • Years matter less to us than trajectory. The typical shape is 3-5 years of engineering experience, but 2-3 unusually fast-growing years count fully if they were spent working directly alongside a staff or principal engineer on a shipped robotics or perception product. Our ideal candidate has been the second chair on a real integration effort - watched how the cross-team calls get made, made a growing share of them under a senior engineer's cover - and is ready to own the whole thing for the first time.

What this role is not:
  • Not a role where you'll personally develop the core SLAM algorithms, train the models, or design the chip. Those are owned by dedicated specialist engineers and teams. Your job is integration and systems and product judgment across their work, not doing their jobs for them.
  • Not a management role. No direct reports today. You will drive alignment and technical decisions across teams you have no formal authority over. The "tech lead" part of this role is earned through judgment and trust, not a title.
  • Not a narrow software engineering role focused on one clean layer of the stack. If you want to specialize in a single domain and hand off everything else, this isn't the right fit.
  • Not a role with mature ML and data infrastructure to inherit. Where that does not exist yet, you are building it, not maintaining someone else's.

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