Autonomous Research Engineer Jobs

Proven ability with large-scale change management

Lead and execute AM qualification models in support of the Brewery’s master plans

4+ years experience across progressive roles in manufacturing direct-leadership, preferably within food and beverage

Past experience with being a site-level Pillar Leader, preferably in two or more pillars

Strong knowledge of Manufacturing Execution Systems (MES); data analysis and interpretation for measures of efficiency, such as OEE, MTBS, MTTF, MTTR

This role will lead the Autonomous Maintenance (AM) Pillar for the company. The AM Manager develops

Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience).

5+ years of relevant research experience in the field of vehicle / robot autonomy.

Excellent collaboration and interpersonal skills

Exceptional programming skills in Python; C++ and parallel programming (e.g., CUDA).

Strong communication and interpersonal skills are required along with the ability to work in a dynamic, research-focused team.

Designing and implementing cutting-edge techniques in the field of vehicle autonomy.

Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience).

5+ years of relevant research experience in the field of vehicle / robot autonomy.

Excellent collaboration and interpersonal skills

Exceptional programming skills in Python; C++ and parallel programming (e.g., CUDA).

Strong communication and interpersonal skills are required along with the ability to work in a dynamic, research-focused team.

Designing and implementing cutting-edge techniques in the field of vehicle autonomy.

Strong proficiency in data warehousing concepts, data modeling, and database management systems.

Create and maintain detailed documentation for data ingestion and serving processes, ensuring knowledge sharing across the team.

Work closely with the AV development team to understand data requirements and contribute to the enhancement of data-driven solutions.

Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).

8+ years of work experience.

Proven experience in designing and building data ingestion pipelines for large-scale systems.

Write safe, highly efficient real-time code in C++, making use of algorithmic parallelism offered by GPGPU programming in CUDA.

BS, MS, or PhD in Computer Science or related fields (or equivalent experience).

2+ years of proven experience.

Experience in computer vision, 3D geometry, mapping, localization or related technologies.

Outstanding communication and teamwork skills, as this project requires both cross-team collaboration and work in a tightly-knit team.

Significant industry experience in above areas.

Excellent C++ programming skills using modern C++ and experience in development on Linux

Developing and optimizing software architecture and frameworks for real-world performance while matching or exceeding customer requirements

Developing highly efficient product code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA).

MS or higher in computer science or related engineering discipline (or equivalent experience)

2+ years of relevant industry experience

Knowledge of Python and its ecosystem for scientific computation

Completing or recently completed a PhD in Robotics, Computer Science, Computer Engineering or related field (or equivalent experience).

Minimum of 3 years of relevant research experience in the field of vehicle / robot autonomy.

Exceptional programming skills in Python; C++ and parallel programming (e.g., CUDA) are a plus.

Knowledge of common machine learning frameworks such as PyTorch and Tensorflow.

Strong communication and interpersonal skills are required along with the ability to work in a dynamic, research-focused team.

Designing and implementing cutting-edge techniques in the field of vehicle autonomy.

Advanced Python programming skills, experience with Python testing and packaging infrastructure, and knowledge of the Python ecosystem

Build your own micro LIMS (Lab Information Management System) & robotic scheduler

Manage flow cytometry, imaging, -omics, and robotic execution data.

Substantially faster iteration loops than big pharma & academic labs

Vertical integration of anything important

Long-term bet on autonomous research systems outperforming humans and improving scientific output in specialized tasks