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Collaborative Robotics

Collaborative Robotics

Hardware and software for human-robot collaboration

AI Research Engineer - Foundational Models AI

Full-Time
No salary listed
Mid
Master's, PhD
Seattle, WA, USA
In Person

On-site at the Seattle office; occasional travel is required. Relocation stipend available for relocations from more than 50 miles away.

About the job

Requirements
  • A Master's degree in Machine Learning, artificial intelligence, Computer Science, or a related technical field is required.
  • At least 3 years of experience in applied machine learning research and software engineering is required.
  • Hands-on experience training large-scale machine learning models, including transformers or diffusion models, is required.
  • Strong understanding of reinforcement learning fundamentals and applications is required.
  • Proficiency in Python and machine learning frameworks such as PyTorch, JAX, or TensorFlow is required.
  • Ability to write clean, efficient, and scalable code that supports fast iteration is required.
  • Ability to collaborate and communicate effectively is required.
  • Willingness to travel occasionally is required.
  • Must have and maintain United States work authorization.
Responsibilities
  • Design, build, and iterate on experimental machine learning pipelines supporting foundational model development.
  • Implement and train large-scale models, including transformers and diffusion-based architectures, for generative and control tasks.
  • Develop and evaluate reinforcement learning algorithms and frameworks for autonomous behaviors.
  • Rapidly prototype and deploy research ideas into working code to accelerate artificial intelligence experimentation cycles.
  • Collaborate with cross-functional teams to integrate machine learning components into real-world systems.
  • Stay current with artificial intelligence research and share insights internally and externally.
Desired Qualifications
  • A PhD in Machine Learning, artificial intelligence, Computer Science, or a related field is preferred.
  • At least 4 years of experience in applied machine learning research and software engineering is preferred.
  • Experience designing machine learning experimentation frameworks and model training pipelines.
  • Practical knowledge of simulation environments or robotics systems.
  • Familiarity with robotic systems or simulation environments.
  • Familiarity with multimodal architectures and imitation learning.
  • Understanding of edge computing or distributed machine learning training infrastructure.

About the company

Collaborative Robotics

Collaborative Robotics

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Collaborative Robotics creates robots that work alongside people by integrating into human environments. Its hardware and software are designed to adapt to different settings in manufacturing, logistics, and healthcare, delivering predictable, trustworthy robot behavior that fits existing operations. The product combines physical robots with software that enables them to understand and respond to real-world workflows, so they can be deployed in diverse applications and deliver measurable ROI. What sets Collaborative Robotics apart is its emphasis on seamless, human-centric integration rather than just automation; its solutions are tailored to work closely with people and current processes. The company aims to make robots natural extensions of human teams, improving efficiency and safety while blending into everyday operations.

Company Size

201-500

Company Stage

Series B

Total Funding

$140M

Headquarters

Santa Clara, California

Founded

2022

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Simplify's Take

What believers are saying

  • Proxie logged 12,627 production hours and moved over 40 million pounds.
  • Gen2 orders start at $5,000 monthly, creating predictable recurring revenue.
  • Existing customers include Maersk, Mayo Clinic, Moderna, Owens Minor, and Tampa General Hospital.

What critics are saying

  • Amazon Robotics keeps launching Proteus, Vulcan, and STARK, squeezing warehouse autonomy budgets.
  • Proxie still depends on complex real-world deployment; one failed site damages credibility quickly.
  • A stalled enterprise rollout leaves Cobot burning cash against better-capitalized rivals like Amazon.

What makes Collaborative Robotics unique

  • Brad Porter’s ex-Amazon Robotics team shipped Proxie into production by June 2026.
  • Proxie Gen2 combines mobility, bimanual manipulation, and autotasking without software integration.
  • NVIDIA Jetson and AWS integration strengthen edge autonomy and fleet learning.

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Benefits

Remote Work Options

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

3%

2 year growth

-2%
PR Newswire
Jun 22nd, 2026
Cobot announces second-generation Proxie, bringing production-tested Physical AI to real operations.

Cobot announces second-generation Proxie, bringing production-tested Physical AI to real operations. Jun 22, 2026, 09:00 ET One production-tested platform combines mobility, bimanual manipulation, and self-directed task execution, deploying in days with no IT integration and no human dispatcher SANTA CLARA, Calif., June 22, 2026 /PRNewswire-PRWeb/ - Collaborative Robotics Inc. (Cobot) today announced the second-generation Proxie, a general-purpose mobile collaborative robot that identifies the work that needs to be done and does it, with zero software integration. Generation 2 is built on the learnings from the first generation Proxie that has now logged 12,627 operating hours in production environments ranging from hospitals to manufacturing to logistics. Often operating 16-hour days, in the past 2 years of operations, Proxie has moved over 40 million pounds of materials and saved over 17 million steps. In production, Proxie builds a real-time world-model (RTWM) of the operations which it then uses to self-identify work that needs to be performed and completes the work autonomously. Cobot calls this capability Autotasking, and it runs with no software integration and no human dispatchers. With over 500 improvements derived from Proxie's experience in the field, Generation 2 is designed for scale-up manufacturing with simplified assembly, 40% fewer parts, and lifecycle-tested components. Gen2 is more compact, saving space in narrow hallways and elevators, while packing more strength to move up to 1,500lb carts and lift up to 200lbs on its vertical spine. Proxie Gen2 moves to lithium iron phosphate batteries for industrial safety and a self-swapping battery station for continuous operation with no downtime. Proxie Gen2 also introduces a modular option for two-armed interactions. Leveraging the latest in physical AI models for dexterous bimanual manipulation, Proxie can quickly be trained to complete complex manipulation tasks reliably. "For decades, deploying robots has meant choosing between mobility and dexterity, and always required custom software integration," said Brad Porter, founder and CEO of Cobot. "Our second-generation Proxie brings all of that together in one platform we designed end-to-end. It moves, manipulates, and orchestrates its own work. The robots identify what needs to be done, announce what they're going to do, and then they just do it." Physical AI on the Robot With its on-robot AI compute, task inference runs locally on Proxie, with no cloud dependency for core task execution. Proxie's ScoutSense sensor technology sees the workplace from human eye level, plans and sequences the work, and audibly announces each action before the robot moves. The new bimanual configuration introduces two arms able to cover a wide array of human-scale, two-handed tasks including hospital resupply, warehouse kitting, life sciences lab operations, and manufacturing line tending. Vista: Orchestration and operational intelligence across the fleet Cobot's Vista AI console gives operators real-time visibility into every task as it is created, queued, and completed, tracks fleet status, and surfaces operational patterns so teams can intervene before issues affect a shift. Where Business Intelligence (BI) tools explain what already happened, Vista manages what is happening now and helps shape what happens next. Built with NVIDIA and AWS Cobot has expanded its collaborations with NVIDIA and AWS. The NVIDIA Jetson platform provides on-robot AI compute for real-time perception, planning, and local task inference, letting Proxie execute core work on the edge. Cobot is also collaborating with NVIDIA Robotics on NVIDIA Isaac Sim and NVIDIA Omniverse NuRec for simulation, turning real-world deployment data into repeatable scenarios that accelerate validation and rollout across customer environments. AWS serves as the cloud backbone for Cobot's fleet-level intelligence, powering Vista and Autotasking, enabling the model training behind Proxie, and turning individual robots into a continuously improving autonomous fleet. "Physical AI is moving into real-world operations, where robots need to understand dynamic environments, reason in real time, and work safely alongside people without months of custom integration," said Amit Goel, head of robotics and edge AI ecosystem at NVIDIA. "Cobot's integration of NVIDIA Jetson for on-robot AI compute and NVIDIA Isaac Sim for simulation and validation helps Proxie move from development to deployment faster, bringing more adaptable automation to hospitals, logistics and manufacturing environments." Availability The second-generation Proxie is available to order now starting at $5,000 per month. Cobot will demonstrate the platform daily at Automate 2026, June 22-25, at McCormick Place in Chicago. Cobot will be in booth #1684 in the Humanoid Pavilion, hosted by NVIDIA. About Cobot Founded by renowned robotics leader Brad Porter, Cobot builds robots that take on the work the world can no longer staff. Through its first robot, Proxie, Digital Pathology Association, Inc. is bringing physical AI into hospitals, warehouses, labs, and factories where work actually happens. Proxie is in production today with enterprise customers across healthcare, manufacturing, and logistics. Cobot is headquartered in Santa Clara, Calif. Learn more at co.bot. Media Contact Megan Maxwell, Cobot, 1 6508106658, [email protected], co.bot SOURCE Cobot

PR Newswire
Nov 20th, 2024
Introducing Proxie, Cobot'S Collaborative Robot, Built For The Real World

SANTA CLARA, Calif., Nov. 20, 2024 /PRNewswire/ -- Collaborative Robotics (known as Cobot), a leader in practical collaborative robots (cobots), and founded by the team that helped scale Amazon Robotics to over 500,000 robots, today announced the public launch of its robot, Proxie. The first of its kind, highly adaptable, collaborative robot takes on the demanding material handling tasks that keep the world moving. Cobot is incredibly proud to count as some of its first customers industry leaders Maersk, Mayo Clinic, Moderna, Owens Minor, and Tampa General Hospital.Meet Our Cobot: Proxie

WTWH Media LLC
Nov 20th, 2024
Collaborative Robotics Unveils Proxie Mobile Manipulator

Listen to this article. Collaborative Robotics Inc. today unveiled its Proxie mobile manipulator publicly for the first time. The startup has been secretive about the design of the robot since Brad Porter founded the company in 2022. Porter has hinted at the design of the robot by alluding to the importance of a mobile manipulator for applications within the warehouse, with a kinematic better suited for warehouse workflows than a humanoid

WTWH Media LLC
Jun 14th, 2024
Collaborative Robotics Expands With New Seattle Office And Ai Team

Listen to this articleCollaborative Robotics has kept its actual robot out of public view. | Source: Adobe Stock, Photoshopped by The Robot Report. Collaborative Robotics, a developer of cobots for logistics, today announced the establishment of a Foundation Models AI team. Michael Vogelsong, a founder of Amazon’s Deep Learning Tech team, will lead the new team in Seattle. “Our cobots are already doing meaningful work in production on behalf of our customers,” stated Brad Porter, CEO of Collaborative Robotics. “Our investment in building a dedicated foundation models AI team for robotics represents a significant step forward as we continue to increase the collaborative potential of our cobots.”

WTWH Media LLC
May 29th, 2024
Robotics Investments Top $466M In April 2024

Listen to this articleFigure 1: Global Robotics Investment – Trailing 12 Months. Robotics investments reached at least $466 million in April 2024, the result of 36 funding rounds. The April investments figure lagged recent months and was the smallest amount since November 2023. April 2024’s investment total was significantly less than the trailing 12-month average of $1.1 billion (see Figure 1). Providers of collaborative robots scored the two largest rounds. As described in Table 1, Collaborative Robotics’ $100 million Series B round was April’s largest investment