Senior Data Operations Engineer

Our Success Criteria

• Participate in data collection sessions to ensure their smooth execution
• Acquire and annotate datasets that align with ML needs
• Develop algorithms to transform robot telemetry into ML training and validation datasets
• Build and support a secure, extensive, scalable, repeatable, and high-performing data collection platform
• Systematically augment datasets in order to increase the accuracy of ML applications
• Build and deploy ML model evaluation pipelines
• Analyze collected data and show how the data contribute to the model performance
• Build and implement tools that will support data analysis


Your Experience
Qualifications:
• Bachelor's degree or higher in Computer Science or related fields
• 5+ years experience in a Data Platform Engineer, DataOps, or equivalent role
• 2+ years of Experience with ML frameworks, platforms and tools
• Basic understanding of machine learning algorithms, including reinforcement learning, behavior cloning, and generative AI
• Knowledge of professional engineering practices for the full product life cycle, including coding standards, code reviews, source management, agile, processes, testing, and operations
• Demonstrated ability to design, implement, and test in a fast-paced environment


Skills:
• Ability to develop data collection efforts that focus on the end-to-end user experience, including anticipating potential failure modes, edge cases, and anomalies
• Demonstrated proficiency with Python for data pipeline development
• Demonstrated experience developing, optimizing, and maintaining data warehouse solutions
• Demonstrated experience with setup and configuration of ML Ops platforms such as Weights & Biases and ClearML
• Demonstrated experience with Observability platforms such as Splunk, Datadog, ELK Stack, and Prometheus/Grafana
• Demonstrated familiarity with MLOps, ML, and deep learning techniques; including but not limited to Computer Vision, SLAM, NLP/NLU, and Robotics


Traits:
• Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems
• Optimistic listening and conflict resolution capabilities
• Strong verbal and written communication and interpersonal skills
• Self-motivated and able to solve problems independently
• Demonstrated ability to communicate to get things done
• Passion for bringing human-like intelligence to machines