Elevate Robotics Inc · 8 hours ago
ML Ops / Data Operations Engineer
Austin, TX
Full-time
Onsite
Mid Level
3+ years expElevate Robotics, Inc. is a subsidiary of Apptronik focused on democratizing mobile manipulation to enhance worker safety and address labor shortages. They are seeking an experienced MLOps / Data Operations Engineer to manage the data foundation for their Vision-Language-Action models, ensuring high-quality datasets are produced for machine learning training.
Industrial Automation
Responsibilities
Design, implement, and maintain processes and tools for collecting training data from robotic systems in real-world environments
Define and enforce data quality standards, validation checks, and acceptance criteria for training readiness
Curate datasets by filtering, cleaning, structuring, and annotating raw sensor data (e.g., images, video, metadata)
Work closely with robot operators and data labeling teams to improve collection protocols, labeling accuracy, and throughput
Develop feedback loops to identify data gaps, failure modes, and distribution issues in existing datasets
Own dataset versioning, lineage, and reproducibility across experiments and model iterations
Build and maintain tooling for tracking dataset provenance, splits, and compatibility with different training runs
Ensure datasets are discoverable, auditable, and easy for ML engineers to consume
Drive strategies to increase effective data volume, including more efficient data collection workflows, smart sampling and filtering, and data augmentation and transformation pipelines
Partner with operations and robotics teams to maximize useful data yield from deployed robots
Work closely with machine learning engineers to understand training requirements, data formats, and failure cases
Translate model performance issues into actionable data collection or curation improvements
Ensure data pipelines align with evolving model architectures and training workflows
Build internal tools, scripts, and services to automate data ingestion, processing, validation, and export
Maintain scalable storage solutions for large datasets (e.g., images, video, logs)
Implement monitoring and metrics for data quality, freshness, and coverage
Support training workflows by enabling reliable access to curated datasets
Assist with scheduling or monitoring large training runs in collaboration with ML engineers
Qualification
Required
Strong software engineering fundamentals (Python required; testing, documentation, version control)
Professional experience in data engineering, MLOps, or ML infrastructure roles
Hands-on experience building data pipelines for large-scale or production ML systems
Experience managing large datasets, including storage, versioning, and validation
Ability to work cross-functionally with ML engineers, robotics teams, and non-software operators
Comfort operating close to real-world systems where data is messy, incomplete, or noisy
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
3+ years of experience in software engineering, data engineering, or ML infrastructure roles
Experience building tools or platforms used by ML engineers or researchers
Preferred
Familiarity with ML training workflows and frameworks (e.g., PyTorch, TensorFlow)
Experience with distributed systems or large-scale data processing
Experience with robotics data (vision, perception, logs, sensor streams)
Experience supporting labeling workflows or annotation tooling
Exposure to training job scheduling frameworks (e.g., Ray, Slurm)
Company
Elevate Robotics Inc
Hard Work. New Heights.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase