Embodied AI Engineer

About the Team - LG's Emerging Technology Lab

LG's Emerging Technology Lab (ETL) is the catalyst for technological innovation within LG’s CTO organization. Located in the Silicon Valley and New Jersey, we drive excellence across CTO organizations and business units by pioneering in select emerging technology areas. As the Center of Excellence (CoE), we define and shape key technology domains, setting strategic directions that foster impactful internal and external partnerships to deliver measurable business value.

 

About the Position – Embodied AI Engineer

We are seeking an exceptional Embodied AI Engineer to build the foundation of LG's vision of the Zero-labor Home. This hybrid role offers a unique opportunity to design, build, and scale the technology and tooling that turn generalist robot intelligence into deployable capability on next-generation LG home robot platforms. You will work at the frontier of embodied AI engineering, building the infrastructure, pipelines, and training systems that let research ideas run at scale and ship into real products used by millions.

What You Will Do

• Implement, debug, and optimize model architectures (VLA, diffusion/flow-matching policies, world models) taking them from prototype to reliable and reproducible systems.
• Build and maintain scalable training and evaluation infrastructure for Robot Foundation Models and on-robot deployment stacks.
• Architect and operate large-scale data pipelines that combine high-fidelity simulation, generative AI, teleoperation, and real-world data collection to fuel model training.
• Work hands-on with robot hardware to bring up new platforms, debug real-world failures, and close the loop between simulation and deployment.
• Collaborate with global research teams and hardware partners to integrate embodied AI systems into LG's consumer ecosystem, and contribute engineering input to technical roadmaps.

Why This Opportunity Is Unique

• Operate at the intersection of frontier AI research and large-scale consumer deployment, where systems you build carry algorithms directly from prototype to product.
• Take ownership of core infrastructure and tooling that the broader research org depends on and contribute with measurable impact.
• Engage with leading industry, university, and startup teams to co-develop hardware–software systems and validate them in real-world conditions.

Expected Qualifications

• Bachelor's degree and 5+ years of relevant industry and/or research experience, or Master's degree and 3+ years of relevant industry and/or research experience, in Computer Science, Mechanical Engineering, Electrical Engineering, or a related technical field. PhD preferred but not required.
• Strong software engineering proficiency in Python or C++, experience working across the full stack from data pipeline to deployed model.

• Hands-on experience with one or more of the following:
• Training and deploying Robot Foundation Models (e.g., VLA, diffusion/flow-matching policies for manipulation or locomotion)
• Building data pipelines for robot learning (simulation, teleoperation, generative data augmentation)
• Developing and maintaining robot system infrastructure for robot manipulators or mobile robots, RGB/Depth cameras, FT/tactile sensors
• Excellent written and verbal communication skills, with the ability to work closely with research scientists and translate ideas into shipped systems.

 

Nice-to-Have

• Familiarity with the robot learning research literature (world models, spatial intelligence, learning from demonstration) sufficient to collaborate closely on architecture decisions.
• Contributions to open-source robotics or ML infrastructure tooling.

Please note: the compensation range is dependent on experience and location.

#LI-JH1  #LI-Hybrid