Machine Learning Engineer: Evaluation

The role

You will build pipelines for measuring system performance across simulation, hardware in the loop, and field data. You will develop metrics, implement data classifiers, and model metrics to predict system performance.

What you will do

• Build pipelines for measuring system performance across open loop and closed loop simulation, hardware in the loop systems, and field data.
• Connect product goals and system behavior by bridging real-world specification to measurable indicators from logged data.
• Implement infrastructure and classifiers to self-annotate data and allow creation of datasets.
• Leverage models to source rich annotations for massive datasets.
• Model metrics and interpret results from various sources ranging from raw sensor data to key leading indicators.
• Determine whether new construction sites pose hidden challenges and drive business decisions about deployment readiness.

Required qualifications

• Senior or Staff level
• 5+ years of professional software engineering, data science, or research experience
• 2+ years of professional experience analyzing modern ML or robotics system performance on real-world problems
• Proficiency in Python
• Proficiency in a data warehouse query language
• Comfort with development on infrastructure within parallelized cloud-based frameworks
• Strong statistical analysis skills (e.g. classification, model fit bias determination, hypothesis testing, and uncertainty quantification)
• Experience working with large datasets

Nice to have

• Engineers who have applied statistical backgrounds to ML research or real-world robotics applications

About the company

Bedrock is bringing autonomy to the construction industry. The team includes veterans from the autonomous vehicle industry.