Robotic AI Engineer/Applied Scientist - Foundation Models

Maven Robotics, Inc.; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Maven Robotics, Inc. seeks an exceptional Robotic AI Engineer/Applied Scientist to design, implement, test, and deploy state-of-the-art foundation models on our robots.

You will develop, fine-tune, and optimize models, build robust pipelines for training and deployment, and collaborate across data, software, and systems teams to achieve real-world impact. You will stay at the forefront of research, incorporating advancements in AI and foundation models to enhance robotic capabilities.

Qualifications

• MS or PhD in CS, ML, or AI required.
• Deep ML knowledge: transformers, attention mechanisms.
• Experience with fine-tuning, RAG, RLHF, or prompt engineering.
• Python proficiency and multimodal foundation models knowledge.

Responsibilities

• Design, implement, test, and deploy foundation models on robots.
• Build training, evaluation, and deployment pipelines.
• Collaborate with data, software, and systems engineers.
• Stay updated with AI advancements and push boundaries.

Skills

ML concepts

Transformers/attention

RAG/RLHF

Python

Multimodal models

Edge deployment

Education

MS or PhD in CS/ML/AI

Tools

PyTorch

TensorFlow

RLHF tooling

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.

In this role, you will:

• 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