Machine Learning Engineer Evaluation

At Bedrock were moving AI out of the lab and into the real world. Our team includes veterans who helped launch Waymo scaled Segment to a $3.2B acquisition and grew Uber Freight to $5B in revenue. Today were deploying autonomous systems on heavy construction equipment across the country improving safety on job sites and accelerating schedules on critical infrastructure projects.

Were not here debating the future of AI. Were deploying it in the real just two years weve raised $350M and achieved the first fully autonomous excavator deployments in construction.

This is where algorithms meet steel-toed boots. Youll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations cant touch. If youre ready to do meaningful work on hard problems wed love to have you join us.

Machine Learning Engineer: Evaluation

Bedrock is bringing autonomy to the construction industry! Were a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market.

Were looking for a highly motivated engineer with experience evaluating complex ML systems deployed in the real Mission: Translate the infinite nuance of the built world into actionable AI-native evaluations that accelerate Bedrock Operator adoption.

The ideal candidate has hands-on experience in building evaluation systems and designing and executing statistical tests to gauge performance deltas between system iterations. More importantly youve iterated on complex ML systems run in production environments and you understand the complexities that come with it.

• Build pipelines for measuring system performance across open loop and closed loop simulation hardware in the loop systems and field data from Bedrock Operator equipped machinery. Excite other teams to gain insights earlier in the development cycle through streamlined workflows.

• 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: Were especially interested in engineers who have applied statistical backgrounds to ML research or real-world robotics applications.

Our roles are often flexible. If you dont fit all the criteria or are in another location (especially one where we have an office like SF or NY) please apply anyway! Wed love to consider you.

Bedrock Robotics is an Equal Opportunity Employer

Were committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race color religion sex sexual orientation gender identity national origin ancestry age disability veteran status genetic information or any other protected characteristic.

Reasonable Accommodations

We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process please let your recruiter know so we can support you.

Required Experience:

IC