Physical Robotics

Physical Robotics builds intelligent humanoid robots that work safely alongside humans in real-world environments. The Pi robot uses force-controlled hands with high-bandwidth sensing, compliant actuators, model-based control, and data-driven policies to enable dexterity. It targets industries like manufacturing and healthcare and integrates with existing workflows and safety requirements. The platform emphasizes Physical Intelligence, transferring skills from simulation to reality. The company aims to scale deployment across logistics, field service, and other contact-rich tasks.

AIDexterityHealthcareHumanoid RoboticsManufacturingPhysical IntelligenceRobot Piphysicalrobotics.com

Physical Robotics

AIDexterityHealthcareHumanoid RoboticsManufacturingPhysical IntelligenceRobot Piphysicalrobotics.com

HQMoss, NO

Team Size11

Open Jobs10

Total Funding$4M

Latest Fundraise6 months ago

Join the Team

Expert AI Engineer/ Robotics

On-SiteHo Chi Minh City, VN

On-Site • Ho Chi Minh City, VN

Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.

Data Scientist

Full-timeNew York, US

Full-time • New York, US

Software Engineer

Part-timeManchester, GB

Part-time • Manchester, GB

Backend Developer

InternshipMunich, DE

Internship • Munich, DE

Data Scientist

ContractHamburg, DE

Contract • Hamburg, DE

Software Engineer

InternshipMunich, DE

Internship • Munich, DE

Software Engineer

ContractCambridge, GB

Contract • Cambridge, GB

Physical Robotics | Norway (Oslo–Viken) | Core Team | Make History

We’re not hiring “an AI engineer.” We’re recruiting a championship AI builder

Humanoid robots will become the next industrial revolution: a new labor layer that can do real work in factories, logistics, and environments humans avoid. Most teams will publish papers or ship demos. A few will build production-grade physical intelligence

that survives the real world.

We’re building that team.

Small team. High standards. Big ambition.

If you want a career where you can point to a new chapter in humanoid AI and say “I built the brain that made it real”

this is it.

The mission

Physical Robotics is a Norway-based humanoid robotics company founded by Dr. Phuong Nguyen

(ex–cofounder of 1X Technologies

) and backed by Skyfall Ventures

together with leading Norwegian industrial partners and investors. Our objective is to build a world-class humanoid

by unifying high-performance hardware

with physical intelligence

-the capability to perceive, plan, and act robustly in real-world environments.

We are building for the next inflection point: broad industrial deployment of humanoids in manufacturing and operations. We expect adoption to accelerate in 2027–2028

, and our strategy is to arrive at that wave with a platform that is production-grade, scalable, and operationally reliable

-not a lab prototype. We benchmark ourselves against the strongest global players- Tesla, Figure, Boston Dynamics, Toyota, Xiaomi, 1X Technologies

-and we intend Physical Robotics to become a reference name the field follows.

At Physical Robotics, we are building the AI foundation

for physical intelligence: Models that don’t just generate text-they perceive

, reason

, plan

, and act

under real-world constraints. This is AI that touches reality: Data quality, latency, safety, distribution shift, evaluation, deployment, and iteration speed.

You will help set the pace, the bar, and the architecture that the company scales on.

What you will own

“Make History” tasks you might lead

Build a training + evaluation pipeline that turns raw multimodal data into reliable policy behavior.

Required (must-have)

Preferred (high-leverage)

The mindset we’re recruiting

You are:

Obsessed with measurable progress

Why Physical Robotics

Core team impact

: your AI decisions define years of platform capability
Real deployment

: your models will run in production pipelines and on real robots
Competitive salary + incentive option program
A chance to build technology the world will copy and to make Physical Robotics a name the field follows

Apply

If you’re driven by hard problems and high standards, apply even if you’re not sure you qualify. If you can solve, learn, and ship, we want to talk.

Send your CV to giang@physicalrobotics.com

Subject: *AI Expert / Senior AI Engineer -Humanoid Robotics - Your Name

Core model strategy

: choosing the right architectures, objectives, and training recipes to win in real-world settings

Distributed training at scale

: multi-node training, performance tuning, memory optimization, reliability of long runs

Post-training + alignment

: fine-tuning, preference optimization / RLHF-style workflows, safety & behavior shaping

End-to-end AI pipeline

: data curation, labeling/filters, training infra, evaluation, deployment, monitoring

Serving & deployment

: low-latency inference, model packaging, versioning, rollout strategy, rollback safety

Real-world integration

: AI that operates inside a robotics stack (latency budgets, failure modes, sensor noise)

Ship a scalable distributed training stack that consistently produces strong models (not one-off runs).

Create post-training workflows that improve capability while keeping behavior stable and aligned.

Deliver a model serving system that meets real-world constraints: latency, uptime, monitoring, safety.

Push the frontier of Physical AI

for humanoid manipulation and autonomy.

Turn “research results” into deployable production artifacts

that run on real robots.

Deep expertise in at least three

areas:

Physical AI / Multimodal LLMs

Hands-on experience with distributed training

and multi-node training

Model training, optimization, serving, and deployment

Experiences in deployment techniques (model serving, designing data pipelines, AI pipelines).

Minimum four years of experience in A.I/ML engineering.

Proficiency in Python and related ML frameworks such as Torch, Tensorflow, and Jax.

Experiences in LLM post-training techniques ( LoRA/QLoRA, RLHF, alignment

Strong understanding of generative AI ( autoregressive model,

diffusion models, flow matching

Experiences in distributed training on large-scale datasets.

Strong background in ML system design,

and understanding MLOPs best practices.

Strong background in Mathematical and Machine Learning.

Master level degree in Computer Science, Mathematics or related field.

Strong publication record (top AI/ML/robotics conferences or journals). Preferred first author of publications in top tier A.I conferences such as Neurips, ICLR, ICML, AAAI, IJCAI, CVPR, ICCV, ACL, BMVC is a plus.

Kaggle experience (competitions, medals, high rankings).

Experience with Vision–Language–Action (VLA)

models.

Experience deploying models into real-world

or robotics systems.

Experience with DeepSpeed

/ Accelerate

is a plus.

PhD in Computer Science, Mathematics or related field.

Understanding of techniques such as test-time scaling

, MoE

, MPO

is a plus.

(not vibes): strong evals, ablations, reproducible wins

Comfortable owning the full loop: data → training → evaluation → deployment → monitoring → iteration

Pragmatic: you can do research-quality work and still ship production systems

Calm under pressure and relentless in debugging distributed training and deployment issues

Motivated by hard problems, not comfort

Ready to earn a seat on a small team doing world-class work

This role is for people who want to compete at the top level because humanoids are a global race.