JOB SUMMARY

Apptronik AI Robotics (AIR) team is building a new generation of world-class large behavior and reasoning models for multi-resolution decision making in Robotics and building production grade robotics solutions and delivering this to customers. Apptronik AI Robotics Ops (AIRops) team is responsible for creating the underlying fabric to enable provisioning of core robotics services, training large-scale foundation models for robotics and performing inference for these models in production.  

Appptronik not only provides solutions but also enables an ecosystem of developers. Apptronik AIR builds tooling to build AI enabled robotics both for internal and external developers, democratizing the ability to create solutions on the Apollo platform. This org is at the forefront of defining and driving our Apollo Platform as a Service (PaaS) strategy and execution.

ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES

This role touches all aspects of the Ops pipeline: DataOps, MLOps and RobotOps

• Design and build the development and production platforms that power our products, enabling reliability and security at scale
• Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.
• Overall, this will require creation of platforms for: Data Management, Model Training & Tracking, Benchmarking & Evals, and Model Serving & Deployment
• Manage and build a diverse team of high performing AI and ML Infrastructure engineers.
• Guide and advise product engineering teams on best practices for ensuring observable, scalable and secure systems.
• Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think

TECH STACK

• Data: Data Storage, Data ETL, Versioning,
• Model Lifecycle management: Development and Training, Versioning and Finetuning
• Workflow design, Experiment Tracking, Validation and Management
• Model Deployment & Serving, Monitoring and Logging
• DevOps for Continual Operation and Scaling
• High performance computing infrastructure

EDUCATION and/or EXPERIENCE

• Have 10+ years of experience in engineering, including 5+ years of leadership experience in infrastructure and software engineering management.
• Take pride in building and operating scalable, reliable, secure systems
• Experience in MLOps and Data Ops lifecycle for large scale AI models - feature engineering, training, validation, tracking, inferencing, experimentation, monitoring, security, Lambda processing, SAGA patterns
• Experience in building data pipelines & warehousing, data extraction as well as data preparation for large-scale machine learning models.
• Experience building out high performance computing infrastructure teams at scale
• Expertise optimizing efficiency of distributed training systems and/or inference systems.
• Care deeply about helping to build a diverse, equitable, inclusive culture
• Are comfortable with ambiguity and rapid change

PHYSICAL REQUIREMENTS 

• Prolonged periods of sitting at a desk and working on a computer
• Must be able to lift 15 pounds at times
• Vision to read printed materials and a computer screen
• Hearing and speech to communicate