Senior Applied Scientist

About the role

This position involves developing and refining machine learning and computer vision models to extract valuable insights from extensive customer interaction data and sensor information. You will contribute to creating end-to-end applications that enhance operational safety, efficiency, and sustainability for industries powering the global economy.

Key facts

What you'll do

• Enhance the performance and accuracy of machine learning and computer vision models, including their retraining and optimization for unique company challenges.
• Contribute to research and development across four product areas: Video-Based Safety, Vehicle Telematics, Equipment Monitoring, and Workforce Apps/Site Visibility.
• Process and analyze petabyte-scale data from company cameras and sensors to build new models.
• Optimize models for efficient inference, both on backend systems and edge devices.
• Collaborate with firmware and full-stack engineering teams to ensure optimal model deployment and cost-effectiveness.
• Stay informed about current research in the field and integrate relevant new technologies.
• Work with product teams to translate user needs into effective machine learning and computer vision solutions.
• Uphold and promote company cultural principles, fostering a collaborative and growth-oriented environment.

Requirements

• Hold a Bachelor's or Master's degree in Computer Science or a related technical field, with a minimum of 5 years of experience in an Applied Scientist, Machine Learning Engineer, or similar Computer Vision role.
• Alternatively, possess a Ph.D. in Computer Science or a quantitative discipline such as Applied Mathematics or Physics, with at least 3 years of experience in Computer Vision.
• Demonstrate strong command of at least one programming language from the following: C++, Golang, Java, or Python.
• Exhibit proficiency with common machine learning frameworks like Spark, TensorFlow, or PyTorch.
• Be familiar with managing data processing and machine learning code using GitHub.
• Possess excellent problem-solving capabilities and the ability to work both independently and as part of a team.

Nice to have

• Experience implementing machine learning models on datasets ranging from 100,000 to over 1 million records, particularly for edge deployments.
• Proven experience in building, deploying, and optimizing machine learning models on edge devices.
• Expertise in state-of-the-art models for road segmentation, object detection, and tracking.
• Experience collaborating with cross-functional teams on project development.
• Comfort with full-stack or backend development to gain a comprehensive understanding of data structures and dependencies.

Skills & tools

• C++, Golang, Java, Python
• Spark, TensorFlow, PyTorch
• GitHub

Practical notes

• This role requires up to 5% travel.
• Relocation assistance is not provided.
• Annual base salary range: $170,170 - $286,000 USD.
• Compensation includes base salary, potential performance-based bonuses, and equity grants.
• Benefits include a professional development stipend and comprehensive health and parental leave plans.
• All offers are contingent on the candidate's legal right to work in the specified location.