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Full Time Ai Robotics Jobs (NOW HIRING)

Figure

Helix AI Engineer, Generative AI

San Jose, CA · On-site

$200K - $400K/yr

Prior work in robotics, embodied AI, or real-world ML systems * Publication record in machine learning, computer vision, or generative modeling The US base salary range for this full-time position is ...

Scout AI

Robotics Software Engineer

Sunnyvale, CA · On-site

$145K - $220K/yr

At Scout AI, we're developing Fury, the first robotic foundation model for defense, to give U.S ... In addition, Scout AI provides comprehensive, top-tier benefits to full-time employees. US Salary ...

RoboForce

AI Resident

Milpitas, CA · On-site

$10K/mo

Why RoboForce RoboForce is an AI robotics company developing Physical AI-powered Robo-Labor for ... months, full-time Compensation: * $10,000 monthly salary Benefits: * Company-provided lunch and ...

Carbon Robotics

Technical Recruiter

Seattle, WA · On-site

$120K - $135K/yr

Carbon Robotics is the leader in physical AI for agriculture, helping farmers become more ... We offer competitive compensation and benefits to our full time US based* employees, including:

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$96K

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How much do full time ai robotics jobs pay per year?

As of Sep 4, 2026, the average yearly pay for full time ai 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 a full time AI robotics job?

A Full Time AI Robotics job involves working as a professional who designs, develops, and maintains robotic systems powered by artificial intelligence. These roles typically require expertise in programming, machine learning, robotics engineering, and sometimes hardware integration. Full-time AI Robotics professionals work on projects like autonomous vehicles, industrial automation, healthcare robots, or research and development. They often collaborate with interdisciplinary teams to build intelligent machines that can perceive, learn, and act in complex environments. The position usually offers a standard workweek and full employee benefits.

What are the key skills and qualifications needed to thrive as a full time AI robotics engineer?

To thrive as a Full Time AI Robotics Engineer, you need a strong background in computer science, robotics, machine learning, and engineering, often supported by a relevant degree such as in electrical engineering, computer science, or robotics. Familiarity with programming languages like Python or C++, robotics platforms such as ROS (Robot Operating System), and experience with AI frameworks like TensorFlow or PyTorch are typically required. Problem-solving ability, creativity, and effective teamwork are crucial soft skills in this field. These competencies enable the design, implementation, and optimization of intelligent robotic systems that function reliably in real-world environments.

What are some common challenges faced by professionals in full time AI robotics roles, and how can they be addressed?

Professionals in full-time AI robotics positions often encounter challenges such as integrating AI algorithms with complex hardware systems, ensuring real-time data processing, and maintaining effective collaboration between multidisciplinary teams (software engineers, mechanical engineers, and data scientists). Addressing these challenges typically requires strong communication skills, a thorough understanding of both robotics hardware and AI software, and continuous learning to keep up with rapid technological advancements. Regular cross-functional meetings and hands-on prototyping sessions can also help streamline problem-solving and accelerate project timelines.

What is the difference between Full Time Ai Robotics vs Full Time Machine Learning Engineer?

AspectFull Time Ai RoboticsFull Time Machine Learning Engineer
Required CredentialsBachelor's or higher in Robotics, AI, or related fields; experience with robotics hardware and softwareBachelor's or higher in Computer Science, AI, or related fields; strong programming and statistical skills
Work EnvironmentHands-on with robotics hardware, sensors, and embedded systems in labs or manufacturing settingsSoftware development, data analysis, and model training primarily in office or remote settings
Employer & Industry UsageManufacturers, research labs, tech companies developing autonomous systemsTech firms, startups, research institutions focusing on AI and data-driven solutions

Full Time Ai Robotics roles focus on integrating AI with robotics hardware, requiring knowledge of both software and physical systems. In contrast, Full Time Machine Learning Engineers primarily develop algorithms and models in software environments. While both roles involve AI, Ai Robotics emphasizes hardware interaction, whereas Machine Learning Engineers concentrate on data and software modeling.

More about Full Time Ai Robotics jobs

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What are the most commonly searched types of Ai Robotics jobs?

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Full Time Ai Robotics jobs near you
Infographic showing various Full Time Ai Robotics job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $96,000 per year, or $46.2 per hour.

Helix AI Engineer, Generative AI

Figure

San Jose, CA • On-site

$200K - $400K/yr

Full-time

Re-posted 28 days ago

Job description

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. Our goal is to build embodied AI systems that can perceive, reason, and act in the real world. Figure is headquartered in San Jose, CA, and this role requires 5 days/week in-office collaboration.
Our Helix team is responsible for developing the core AI systems that power humanoid autonomy. We are looking for a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. This role focuses on training and deploying diffusion and generative models across vision, video, and multimodal domains, with applications spanning perception, data generation, and model-based reasoning.
Responsibilities
  • Design, train, and deploy large-scale generative models, with a focus on diffusion-based approaches for vision, video, and multimodal data
  • Develop models that improve robot perception, world modeling, and prediction from raw sensory inputs
  • Build generative systems for synthetic data creation, augmentation, and dataset scaling for robot learning
  • Explore and implement state-of-the-art techniques in diffusion, generative modeling, and multimodal foundation models
  • Optimize training pipelines for large-scale generative models across distributed systems
  • Work closely with data, training infrastructure, and agent teams to integrate generative models into the full autonomy stack
  • Evaluate model quality, robustness, and generalization across real-world scenarios
  • Contribute to the design of scalable experimentation frameworks for generative model development
Requirements
  • Experience training and deploying generative models (diffusion, autoregressive, or related approaches) at scale
  • Strong understanding of modern deep learning techniques for vision and/or multimodal systems
  • Proficiency in Python and deep learning frameworks such as PyTorch
  • Experience working with large-scale datasets and distributed training systems
  • Strong experimental rigor and ability to iterate quickly on model performance
  • Solid software engineering skills and ability to build reliable, maintainable systems
  • Ability to operate independently and own ambiguous, high-impact technical problems
Bonus Qualifications
  • Experience with diffusion models for image or video generation
  • Experience with multimodal foundation models (vision-language or vision-language-action)
  • Background in synthetic data generation or simulation for robotics or embodied AI
  • Experience optimizing large-scale training (multi-node, GPU clusters, etc.)
  • Familiarity with 3D, video prediction, or world models
  • Prior work in robotics, embodied AI, or real-world ML systems
  • Publication record in machine learning, computer vision, or generative modeling

The US base salary range for this full-time position is between $200,000 - $400,000
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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