Machine Learning Engineer: Evaluation
Bedrock Robotics Inc8 months ago
San Francisco, CA, USA or New York, NY, USASenior / Staff+
H1B sponsor
Responsibilities
- Build and maintain performance-measurement pipelines across open-loop and closed-loop simulation, hardware-in-the-loop systems, and field data from autonomous machinery.
- Develop measurable indicators from logged data that connect product goals with system behavior and support decisions from parameter tuning through program planning.
- Implement infrastructure and classifiers to self-annotate data and create datasets for training and evaluation use cases.
- Model metrics and interpret results from raw sensor data and leading indicators to identify site-specific challenges and assess deployment readiness.
- Collaborate with construction experts and engineering teams to improve evaluation workflows and accelerate machine learning system iteration.
Requirements
- Currently operating at the Senior or Staff level with 5+ years of professional software engineering, data science, or research experience.
- At least 2 years of professional experience analyzing modern machine learning or robotics system performance on real-world problems.
- Proficiency in Python and a data warehouse query language, with comfort developing infrastructure in parallelized cloud-based frameworks.
- Strong statistical analysis skills, including classification, model-fit bias determination, hypothesis testing, and uncertainty quantification.
- Experience working with large datasets.
- A statistical background applied to machine learning research or real-world robotics applications is preferred.
Benefits
- Flexible role arrangements and consideration for candidates in locations with Bedrock offices, including San Francisco and New York.
Tech Stack
Categories
ML EngineeringRobotics
About Bedrock Robotics Inc
Bedrock Robotics builds autonomous control systems that retrofit heavy construction equipment, enabling driverless operation on large infrastructure and industrial projects. The San Francisco–based, privately held company, founded in 2024, deploys its technology with contractors and project owners to speed schedules and improve job-site safety. Its business centers on upgrading existing fleets and operating them in the field, with software, sensors, and integration services tailored to construction workflows.