ROLE Robotic AI Engineer/Applied Scientist - Foundation Models Develop and implement foundation models for robots

Maven Robotics, Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 210,000 - 270,000; Full time

Job summary

Maven Robotics, Inc. is seeking an exceptional AI Foundation Model Engineer to design, implement, test, and deploy state-of-the-art foundation models on our robots.

You will develop, fine-tune, and optimize models using methods like pretraining, fine-tuning, and RAG, and build end-to-end pipelines for training, evaluation, and deployment across platforms.

Qualifications

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Deep understanding of machine learning concepts, including attention mechanisms, transformers, and training techniques.
• Experience with fine-tuning, retrieval-augmented generation (RAG), prompt engineering, or RLHF.
• Proficiency in programming languages and tools commonly used in ML (Python).
• Strong grasp of theoretical concepts and practical implementation of multimodal foundation models.

Responsibilities

• Design, implement, test, and deploy state-of-the-art foundation models on robots.
• Develop and optimize foundation models using pretraining, fine-tuning, and RAG techniques.
• Build pipelines for training, evaluation, and deployment across platforms.

Skills

Deep learning

Transformers

RAG

RLHF

Python

Education

MS or PhD in CS/ML/AI or related

Tools

PyTorch

TensorFlow

CUDA

Job description

Robotic AI Engineer/Applied Scientist - Foundation Models

LOCATION:

Role Description

We are seeking an exceptional AI Foundation Model Engineer to design, implement, test, and deploy state-of-the-art foundation models on our robots.

• Develop, fine-tune, and optimize foundation models for the robot, leveraging advanced techniques such as pretraining, fine-tuning, and retrieval-augmented generation (RAG).
• Translate high-level application goals into foundational AI solutions, delivering robust and scalable models that perform effectively in real-world scenarios.
• Build pipelines for training, evaluation, and deployment of models on various platforms, ensuring high performance and adaptability across diverse use cases.
• Stay at the forefront of research, incorporating cutting‑edge advancements in AI and foundation models to enhance system capabilities and push technical boundaries.
• Own critical projects end‑to‑end, from model design and experimentation to deployment and continuous improvement.
• Collaborate with cross‑functional teams, including data, software, and systems engineers, to integrate models seamlessly into production workflows.

Qualifications

Must-have:

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Deep understanding of machine learning concepts, including attention mechanisms, transformers, and training techniques
• Experience working with fine-tuning, retrieval-augmented generation (RAG), prompt engineering, or reinforcement learning with human feedback (RLHF).
• Proficiency in programming languages and tools commonly used in machine learning (e.g. Python).
• A strong grasp of theoretical concepts and practical implementation of multimodal foundation models.

Nice-to-have:

• Experience with deployment of models to edge devices for real-time inference.
• Experience with large-scale distributed training and optimization frameworks (e.g. PyTorch, TensorFlow) and familiarity with tools for model compression and quantization
• General knowledge of robotics principles, including kinematics, dynamics, and control.
• Publications or contributions to the machine learning community, particularly in areas related to robotics or large language models.
• Excellent problem‑solving skills, with the ability to innovate and experiment with novel approaches