Are you passionate about advancing the state of artificial intelligence and machine learning? Our rapidly growing startup is seeking an AI Research Engineer to join our Foundational Models AI team. This role is ideal for researchers and builders who thrive at the intersection of machine learning research and software engineering—those who can turn innovative ideas into working prototypes that push the boundaries of what’s possible in intelligent systems.
In this role, you’ll work closely with a small, dynamic team of AI researchers and engineers exploring reinforcement learning, transformer-based architectures, and diffusion models. You’ll be expected to design, implement, and iterate on ML experiments rapidly, contributing to foundational model development that will shape the future of autonomous systems and intelligent robotics.
Join us to reimagine the future of human-robot interaction.
Collaborative Robotics is a team of innovators and builders redefining the future of human-robot interaction. We are working to realize a world where robots are a trusted extension of your surroundings. They work, adapt, and react around you. Not the other way around.
Design, build, and iterate on experimental ML 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 AI experimentation cycles.
Collaborate with cross-functional teams to integrate ML components into real-world systems.
Stay at the forefront of the latest AI research and share insights internally and externally.
Master’s degree in Machine Learning, AI, Computer Science, or a related technical field.
Minimum 3 years of experience in applied ML research and software engineering.
Hands-on experience training (not just using) large-scale ML models such as transformers or diffusion models.
Strong understanding of reinforcement learning fundamentals and applications.
Proficiency in Python and ML frameworks such as PyTorch, JAX, or TensorFlow.
Proven ability to write clean, efficient, and scalable code that supports fast iteration.
Excellent collaboration and communication skills.
PhD in Machine Learning, AI, Computer Science, or related field.
4+ years of experience in applied ML research and software engineering.
Experience designing ML experimentation frameworks and model training pipelines.
Practical knowledge of simulation environments or robotics systems.
While direct robotics manipulation experience is not required, familiarity with robotic systems or simulation environments is a plus.
Familiarity with multimodal architectures and imitation learning.
Understanding of edge compute or distributed ML training infrastructure.
Cobot is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.
To all recruitment agencies: Cobot does not accept agency resumes. Please do not forward resumes to our employees. Cobot is not responsible for any fees related to unsolicited resumes.
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