Robotics and Machine learning Engineer
Listed on 2026-06-18
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Engineering
Robotics, AI Engineer (Applied/Software)
Overview
Req DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Robotics and Machine learning Engineer to join our team in Plano, Texas (US-TX), United States (US).
Description Applied Robotics & Physical AI Innovation Engineer:
This role evaluates advanced robotic technologies, studies the integration of machine learning and Gen AI models and how they will enable robots to perceive, reason, and act autonomously. The team member will support NTT DATA industry experts in positioning how this technology will impact business in the near and far terms. This hands‑on position will drive our robotics strategy by designing, developing, and implementing cutting‑edge robotic systems that are set to redefine industry standards.
The advisor will also determine how to enhance and improve the current autonomous solutions currently in play. This is a combination research, consulting and deployment roles.
The NTT Data NA Innovation Center seeks an Applied Robotics & Physical AI Engineer to evaluate and develop cutting edge robotic applications and advancing current autonomous solutions. Responsibilities include researching emerging technologies in the field of robotics, understanding the impact of the robotics technology to humans, presenting ideas, collaborating globally, and applying innovations to client needs, strong communication, problem‑solving skills, and potential travel of 25‑35%.
Location:
Plano, Texas – This role requires this individual to be in the office working with the innovation team members and technologies.
- Research emerging technologies in this stated field, document and present ideas for consideration by the NA innovation team
- Weekly presentations of ideas and interacting with technology with clients
- Develops a growth pipeline with the client executives for engagements for tech showcases, workshops and technology evaluations/Po Cs
- Collaborate with vertical and horizontal team SMEs globally
- Ability to apply suggested ideas to client needs and challenges to NTT DATA digital discussions and offerings
- Hands‑on development with mobile robots, quadrupeds, humanoids, and industrial/collaborative robotic arms (e.g., Unitree, humanoid platforms, FANUC-style arms, ROS-based systems). Tooling Experience like: ROS/ROS3, Gazebo/Issac Sim/Mu Jo Co and understanding of real‑to‑sim workflows.
- Experience w/ sensors like LiDAR, depth cameras, IMU’s, information clearly and effectively to business leaders.
- Proficient in computer‑aided design (CAD) software and programming languages such as C++, Python, and Java.
- Develop and integrate AI/ML and Generative/Foundation models for perception, mapping, task planning, and embodied decision‑making.
- Fine‑tune or adapt Generative/Foundation models (Small Language Model/ Small‑Vision‑Language/ Vision‑Language‑Action) models for edge deployment for real‑world robotic applications.
- Strong analytical and problem‑solving skills, with a proven ability to tackle complex engineering challenges.
- Excellent communication and interpersonal skills, with the ability to convey technical
- Ability to work both independently and collaboratively within multidisciplinary teams.
- Bachelor’s in Computer Science, Machine Learning, AI, Robotics, or related field
- 3 years of experience building robotics/Physical AI systems. Exceptional hands‑on builders with strong demo portfolios are encouraged regardless of actual years.
- Familiarity with industry safety standards and regulations pertaining to robotic systems.
Where required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting pay range for this remote role is $100,005 – $157,004. This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on a number of factors, including the candidate’s actual work location, relevant experience, technical skills, and other qualifications.
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