Robot Data Collection Lead

Key Skills

Apache Hadoop, Apache Kafka, Docker, Kubernetes-K8s, MLOps tools, PyTorch, SPARK Programming, TensorFlow

Job Description

Our mission is to solve the most important and fundamental challenges in AI and Robotics to enable future generations of intelligent machines that will help us all live better lives.

As our Robot Data Collection Lead, you will be spearheading initiatives to collect crucial robot trajectory examples, shaping the data's trajectory in our machine learning models. A large part of this role will be coordinating and training robot data collectors and then integrating the resulting logs back into our data platform. If you are fervent about capturing essential data for robot technology, optimizing its quality, and facilitating the development of intelligent machines, this position is tailor-made for you.

Responsibilities

• Coordinate and lead a team of interns or technicians for streamlined collection of robot trajectory examples.
• Design and implement efficient and robust data collection processes tailored to the needs of the robot's functions.
• Collaborate with the data platform team to ensure seamless data integration, storage, and retrieval processes.
• Develop methods for validation and verification of collected data, ensuring accuracy and reliability.
• Oversee data preprocessing and cleansing to improve quality and compatibility.
• Handle any challenges or issues related to data collection, equipment malfunction, or field challenges.
• Construct and manage a comprehensive data repository that can be easily accessed by our research and development teams.

Requirements:

• Experience leading a team, ensuring clear communication and efficient task management
• 5-8 years of experience in data collection, preferable in robots or related field
• Proven Expertise in designing and overseeing data collection processes
• Familiarity with database management, data preprocessing, and validation techniques
• Experience interfacing with data platforms and ensuring smooth data transfer processes

Nice to have:

• Candidates who lack these should not be discouraged from applying
• Hands on experience with MLOps tools and practices
• Familiarity with big data batch and real-time data processing (e.g., Hadoop, Spark, Kafka).
• Prior experience in a robotic or AI-related field
• Experience with Docker, Kubernetes, or similar applications
• Familiarity with deep learning frameworks such as PyTorch or TensorFlow

We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.