Role

As a Senior Research Engineer focused on Data Engine, you will be responsible for the design and implementation of systems that enable the training, deployment, and utilization of large-scale AI models for robotics. You will guide technical direction, mentor engineers, and ensure the development of robust, scalable data pipelines and ML infrastructure required to make robots significantly more capable in real-world environments. Your work will empower both internal teams and external partners by providing accessible tools and infrastructure for injecting advanced machine learning techniques into robotic applications.

How your work moves the mission forward

• Lead the design and implementation of infrastructure for training and deploying large-scale robotic foundation models.
• Oversee the building and maintenance of data pipelines for collecting, processing, and feeding real-world robot data into machine learning workflows.
• Empower ML researchers and engineers with accessible tools and infrastructure for developing and applying AI techniques in robotics.
• Collaborate with product and engineering teams to define infrastructure requirements and deliver successful solutions for partners and customers.

Skills you will need to be successful

• Four-year degree in Computer Science.
• Experience collaborating on medium to large software projects for at least 4 years.
• Experience in programming Python / C++.
• Experience with machine learning (Tensorflow, JAX), cloud computing and containerization (Google Cloud, Docker, Kubernetes), database (SQL, no-SQL), and service-oriented architecture frameworks.
• Proven ability to work with a team, setting directions and driving towards solutions.

Skills that will differentiate your candidacy

• PhD in Computer Science / Engineering with a specialization in Machine Learning and / or Robotics.
• Academic track record of publications in the field of Machine Learning and / or Robotics.
• Experience with Robotic Foundation Models / Vision-Language-Action Models.
• Experience with deploying ML services at scale.

Role

As a software engineer focused on MLOps and deep learning infrastructure, you will design and build the foundational systems that empower robots with advanced machine learning capabilities. You will work within a cross-functional team of engineers and researchers to develop infrastructure that streamlines the training, evaluation, and deployment of large-scale AI models. Your efforts will provide accessible tools for injecting machine learning techniques into the Intrinsic stack, managing compute resources across cloud and on-premise environments, and ensuring that complex model lifecycles are efficient, reliable, and scalable for real-world industrial applications.

How your work moves the mission forward

• Design and implement scalable infrastructure for training and deploying deep learning models on top of a real-time robotic control stack.
• Help optimize data loading and training speed across 1000+ GPU training jobs.
• Build data pipelines that support distributed computing to process large volumes of robotics data for model training.
• Develop APIs and tools that allow internal and external researchers to easily integrate machine learning techniques into their workflows. This could involve leading efforts  to open source models and engage with the community.
• Optimize the allocation of compute resources, such as GPUs and TPUs, to reduce cost and latency during model development and create orchestration workflows to successfully run jobs on GKE.
• Create tools for model understanding and analysis to ensure reliability and traceability across the machine learning lifecycle.

Skills you will need to be successful

• Bachelor's degree in Computer Science, Robotics, Machine Learning, or a related technical field.
• 2 years of experience in software development with a focus on MLOps or machine learning infrastructure.
• Proficiency in programming with Python and C++.
• Experience with containerization and orchestration technologies, specifically Docker and Kubernetes.
• Experience with deep learning frameworks such as TensorFlow, JAX, or PyTorch.
• Experience with cloud computing platforms like Google Cloud Platform.
• Basic Front-end experience.

Skills that will differentiate your candidacy

• Master’s degree or PhD in Computer Science, Robotics, or a related field.
• Comprehensive knowledge of the entire image processing workflow, from initial sensor data acquisition (drivers, OS) up to the final application logic and decision-making.
• Experience with MLOps toolkits such as Kubeflow.
• Hands on experience with CUDA optimization or deep learning optimization. 
• Experience deploying machine learning models at scale in production environments.
• Familiarity with robotics systems or industrial automation hardware.
• Practical experience debugging distributed systems and optimizing network performance.
• Experience with accelerator orchestration (e.g., XManager).

Role

As a Senior Research Scientist focused on Robotic Foundation Models, you will be responsible for the design and implementation of systems that enable the training, deployment, and utilization of large-scale AI models for robotics. You will guide technical direction, mentor engineers, and ensure the development of robust, scalable ML models  required to make robots significantly more capable in real-world environments. Your work will empower both internal teams and external partners by providing accessible tools and infrastructure for injecting advanced machine learning techniques into robotic applications.

How your work moves the mission forward

• Lead the design and implementation of infrastructure and architecture of large-scale robotic foundation models.
• Oversee the training and deployment of robust ML models for high-performance robotic applications.
• Empower ML researchers and engineers with accessible tools and infrastructure for developing and applying AI techniques in robotics.
• Collaborate with product and engineering teams to define infrastructure requirements and deliver successful solutions for partners and customers.

Skills you will need to be successful

• PhD in Computer Science / Engineering with a specialization in Machine Learning and / or Robotics.
• Experience collaborating on medium to large software projects for at least 4 years.
• Experience in programming Python / C++ and machine learning frameworks (Tensorflow, JAX).
• Demonstrable experience with offline Reinforcement / Imitation Learning in a robotics context.
• Proven ability to work with a team, setting directions and driving towards solutions.

Skills that will differentiate your candidacy

• Academic track record of publications in the field of offline Reinforcement / Imitation Learning in Robotics.
• Experience with Robotic Foundation Models / Vision-Language-Action Models.
• Experience with Online Reinforcement Learning and / or Computer Vision for Robotics.
• Experience with deploying ML services at scale, e.g., via cloud computing and containerization (Google Cloud, Docker, Kubernetes), databases (SQL, no-SQL), and service-oriented architecture frameworks.

Role

As a Senior Research Scientist in the Applied Research team, you conduct applied research and design innovative algorithms in the space of geometric computer vision and image/video/vision-centric foundation models for deployment in industrial robotics at scale. In this role you define processes and develop approaches in Deep Learning that mitigate the risks of hallucinations, improve accuracy and deploy algorithms on industrial robotics workcells to gauge sim-to-real transfer of models. As a Senior Research Scientist at Intrinsic you provide input and guidance for the development and generation of synthetic data and annotations required for training foundation models at scale based on the identification of gaps in the sim-to-real transfer of models. You also work with Research partners and cross-disciplinary engineering teams to ideate new approaches and architectures to bring state of the art foundation models to real-world industrial applications. Constant learning and exploration of unfamiliar technologies is also part of this role. 

How your work moves the mission forward

Your work can play a significant role in democratizing access to advanced AI skills to the average user in robotics and enhance the credibility of deploying AI models at scale in industrial settings. As part of your day-to-day work: 

• You are insightful and innovative, proactively identifying needs and bottlenecks based on customer problems and proposing practical solutions that are deployable in high throughput environments.
• You serve as the nexus between the robotics team and our research partners—collaborating with them, providing engineering insights into research projects, and ideating practical next generation solutions. 
• You serve as an advisor to the engineering and other cross-functional teams providing critical guidance in terms of translating early (AI-powered) research capabilities into robust engineering capabilities in Flowstate (Intrinsic’s software platform for robotics solutions).
• You continually keep abreast of the latest developments in deep learning, AI, machine learning, perception to ensure that Intrinsic can continually keep evolving its advanced capabilities over time.
• Document and develop the prototype fully so it can be shipped to external users. 

In all the above, you will work closely with a sub-team within the R&D division, but will also frequently collaborate with other engineering, and product groups within Intrinsic.

Skills you will need to be successful

• Master’s or PhD degree in Computer Science, Robotics, or a related technical field with a high degree of passion for robotics and foundation models and a strong inclination towards accelerating the deployment of such models in practical industrial manufacturing applications.
• 3 years of experience in robotics software development or research (work on your PhD can count towards this).
• Proficiency programming in Python and at least one of the ML/DL frameworks such as PyTorch, Jax, and/or Tensorflow.
• Knowledge of robotics perception or manipulation algorithms.
• Experience working with robot hardware or simulation environments.
• A team player with a product mindset, a willingness to learn, and apply oneself to delivering value in practical real-world problems.

Skills that will differentiate your candidacy

• Advanced degree (Master's or PhD) in Robotics, Computer Science, or a related technical field.
• Expertise in deep learning, including transformer-based approaches for robotics, and other areas such as Learning from Demonstrations, Reinforcement learning.
• Proven ability to apply robotics ML/AI research to real-world problems and demonstrate tangible impact.
• Experience generating or utilizing synthetic data for machine learning in robotics.
• Publications in relevant robotics conferences or journals.