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Dyna Robotics Jobs (NOW HIRING)

DYNA Robotics Inc

AI Data Strategist

Redwood City, CA · On-site

$148.80K - $192.20K/yr

Dyna Robotics makes general-purpose robots powered by a proprietary embodied AI foundation model that generalizes and self-improves across varied environments with commercial-grade performance. Dyna ...

ARA

Staff FEA Engineer 1

Albuquerque, NM · On-site

Develop new material constitutive models for LS-DYNA based on available test data and engineering ... robotics. At ARA, employees are our greatest assets. The corporation realizes that employee ...

ARA Brand

Staff FEA Engineer 1

Albuquerque, NM · On-site

Develop new material constitutive models for LS-DYNA based on available test data and engineering ... robotics. At ARA, employees are our greatest assets. The corporation realizes that employee ...

New

ARA

Staff FEA Engineer 1

Albuquerque, NM · On-site

Develop new material constitutive models for LS-DYNA based on available test data and engineering ... robotics. At ARA, employees are our greatest assets. The corporation realizes that employee ...

Apptronik

Hardware Simulation Manager

Austin, TX

Robotics Simulation: Lead the multi-body dynamics and kinematic simulations to validate joint loads ... Extensive historical experience with industry-standard solvers (Ansys, Abaqus, LS-DYNA, Nastran ...

Apptronik

Hardware Simulation Manager

Austin, TX · On-site

Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting ... Extensive historical experience with industry-standard solvers (Ansys, Abaqus, LS-DYNA, Nastran ...

Encord

GTM Special Projects, Physical AI

New York, NY · On-site

... robotics companies, autonomous vehicle programs, and research-driven enterprises like Boston Dynamics and Dyna. By day 30, you will have identified target accounts and booked meetings; by day 90, you ...

Lego

Technical Project Manager - Logistical

Richmond, VA · Hybrid

$115.80K - $173.71K/yr

Installation management and system troubleshooting for driven conveyors, VRCs, ASRSs and six-axis robots. Manage suppliers with a focus on safety. Effectively communicate technical details to a broad ...

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How much do dyna robotics jobs pay per year?

As of Jun 3, 2026, the average yearly pay for dyna robotics in the United States is $96,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $102,000.00 per year, depending on experience, location, and employer.

What is the difference between Dyna Robotics vs Robotics Technician?

AspectDyna RoboticsRobotics Technician
Required CredentialsTypically requires a degree in robotics, mechatronics, or related field; certifications in robotics or automation are commonUsually requires an associate's or bachelor's degree in robotics, electronics, or similar; certifications like FANUC or ABB are advantageous
Work EnvironmentDesign, develop, and test robotic systems in labs or manufacturing settingsInstall, maintain, and repair robotic systems on production floors
Industry UsageUsed in research, development, and manufacturing industriesPrimarily employed in manufacturing, automation, and industrial settings

While both roles involve working with robotic systems, Dyna Robotics typically focuses on designing and developing robots, whereas Robotics Technicians are more involved in installation, maintenance, and troubleshooting of robotic equipment in industrial environments.

More about Dyna Robotics jobs
What cities are hiring for Dyna Robotics jobs? Cities with the most Dyna Robotics job openings:
What states have the most Dyna Robotics jobs? States with the most job openings for Dyna Robotics jobs include:
What job categories do people searching Dyna Robotics jobs look for? The top searched job categories for Dyna Robotics jobs are:
Dyna Robotics jobs near you
Infographic showing various Dyna Robotics job openings in the United States as of May 2026, with employment types broken down into 9% Locum Tenens, 4% As Needed, 22% Full Time, 57% Part Time, 3% Temporary, and 5% Nights. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $96,000 per year, or $46.2 per hour.

AI Data Strategist

DYNA Robotics Inc

Redwood City, CA • On-site

$148.80K - $192.20K/yr

Full-time

Posted 13 days ago

Job description

Join us to shape the next frontier of AI-driven robotics!
Dyna Robotics makes general-purpose robots powered by a proprietary embodied AI foundation model that generalizes and self-improves across varied environments with commercial-grade performance. Dyna's robots have been deployed at customers across multiple industries. Our frontier model has the top generalization and performance in the industry.
The Role
We are hiring an AI Data Strategist to define the data requirements that drive model improvement across Dyna's robotics platform.
This is a senior individual contributor role that focuses on strategy rather than managing operational execution. Instead of running the day-to-day data pipeline, you will define what operations and research execute against. You will establish the specifications, frameworks, and feedback loops that determine whether our data actually improves our models.
The core question you will help answer every week is: our model failed here, so what does that mean for our data strategy?
What You'll Do
  1. Define Data Collection Priorities
    • Identify lifecycle gaps: Maintain a clear, comprehensive view of where the data lifecycle has gaps, from pre-training through post-training.
    • Direct collection efforts: Prioritize what the data collection team should focus on next, clearly distinguishing between data that merely adds volume and data that actually drives model performance.
  2. Design Evaluation & Quality Frameworks
    • Set the standard: Define how robot episodes should be labeled and determine what rubrics and taxonomies capture meaningful signal.
    • Establish quality benchmarks: Define what "good data" looks like for each task and model stage so the labeling team can execute flawlessly against your standards.
  3. Extract Signal from Operations
    • Translate field realities: Partner closely with the operations team to understand what is happening in the field, including shift handoffs, collection quality, and deployment issues.
    • Inform data strategy: Act as a strategic consumer of operations output, translating real-world operational realities into high-impact data strategy decisions without directly managing the operations team.
  4. Build Data Lifecycle Observability
    • Define health metrics: Establish the metrics that measure the health of each phase of the data pipeline, including collection coverage, label quality, evaluation consistency, and model feedback loops.
    • Drive visibility: Create a real-time, organization-wide view of data lifecycle health.

Who You Are
  • Systems Thinker: You understand that superior models come from exceptional data strategy, not just massive data volume.
  • Structured Problem Solver: Highly analytical and detail-oriented, with the ability to translate messy, real-world failures into structured frameworks.
  • Analytically Minded: Possess strong instincts for failure analysis, dataset structure, and the feedback loops between deployment and training.
  • Cross-Functional Influencer: Able to rally and influence cross-functional teams without needing direct authority.
  • Clear Communicator: Strong written and verbal communication skills, with the ability to prioritize effectively in fast-moving environments where everything feels urgent.
What You'll Bring
  • Core Experience: 4-8+ years of experience working in AI/ML, robotics, autonomy, or data-centric systems roles.
  • Data Strategy Expertise: Proven experience defining data quality standards, evaluation frameworks, annotation systems, or data strategy for machine learning products.
  • Collaborative Track Record: Experience working closely with cross-functional teams, including ML researchers, operations, annotation teams, and engineering.
  • Edge-Case Proficiency: A deep understanding of how deployment failures, edge cases, and real-world operational data translate into model training and evaluation improvements.
Bonus points for
  • Experience operating in fast-moving, ambiguous startup or R&D-heavy environments
  • Experience with embodied AI, video, or time-series data.
  • Familiarity with evaluation pipelines, active learning, or data-centric AI.
  • Exposure to annotation tooling such as Labelbox, Scale, CVAT, Encord, or Voxel51.

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