Machine Learning Engineer: Evaluation

Connect product goals and system behavior - by bridging real-world specification to measurable indicators from logged data. Empower confident decision making from parameter tuning to program planning by slicing through the noise and delivering objective insights.

Implement infrastructure and classifiers - to self-annotate data and allow creation of datasets for a variety of training and evaluation use cases. Leverage models to source rich annotations for massive datasets to accelerate model iteration.

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.

Engineers who are currently Senior or Staff level with 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 and a data warehouse query language and 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

Bonus points: We’re especially interested in engineers who have applied statistical backgrounds to ML research or real-world robotics applications.

Bedrock Robotics is an Equal Opportunity Employer

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