About CompScienceAt CompScience, we're not just building software-we're saving lives. We're a high-growth startup on a mission to prevent 10 million workplace injuries through bold technological innovations, ensuring that everyone can go home safe at the end of the day.Founded in 2019 and backed by investors from SpaceX, Tesla, and Anduril, we've assembled a powerhouse team that bridges two worlds:Cutting-Edge Technology: Our engineering team is comprised of distinguished computer vision engineers, software architects, and data scientists from the self-driving car industry. They bring unparalleled expertise in AI and machine learning to the realm of workplace safety.Insurance Acumen: Our insurance team comprises seasoned professionals who understand the nuances of workers' compensation policies. They work hand-in-hand with our tech experts to translate advanced analytics into tangible insurance products that truly serve our clients' needs.Our groundbreaking perception-based risk assessment program, the first of its kind, provides the most comprehensive data stream available for risk analysis and monitoring and has proven to significantly reduce accidents in some of the world's most hazardous occupations.About the roleWe are looking for an outstanding Computer Vision Engineer to research and deploy new methods for generating deep contextual insights from video data. The causal risk factors that you develop will prevent millions of people from getting hurt on the job. This is a hands-on position requiring the ability to design, develop, and implement solutions individually and with a team.ResponsibilitiesDevelop and implement state-of-the-art computer vision algorithms for object detection, tracking, and action recognition using PyTorchResearch the latest advancements in computer vision and machine learning, adapting promising techniques to our specific use casesPerform data analysis and feature engineering to enhance model performance and accuracyCollaborate with the data collection team to define requirements and improve data quality for training and validationOptimize models for real-time performance and deploy them in production environmentsDevelop metrics and conduct thorough evaluations to measure model performance and impact on workplace safetyRequired experienceMaster's or PhD in Computer Science, Computer Engineering, or related fieldProven track record in developing and deploying computer vision models in production environmentsExtensive experience with PyTorch and computer vision librariesStrong programming skills in Python and C++Solid understanding of machine learning principles and their application to real-world problemsExcellent problem-solving skills and attention to detailStrong communication skills and ability to work in a collaborative, fast-paced environmentNice-to-haveExperience in Linux environment and competence in selecting appropriate hardware for running ML models with desired latency.Experience in data science and methods of ML Ops.What sets this role apartYou'll be at the forefront of AI-driven workplace safety, using our proprietary computer vision solutions to analyze risks and drive meaningful change in workplace safety. Additionally, as a fully remote workplace, CompScience allows all employees to work from home five days/week.Working at CompScienceCompensation: CompScience is committed to fair and equitable compensation practices. The annual salary range for this role is $148,000 - $210,000. Compensation is determined within the range based on your qualifications and experience. Our total compensation package also includes equity and comprehensive benefits.Benefits at CompScience:Fast-paced startup environment where your ideas can quickly become realityOpportunity to wear multiple hats and grow beyond your job descriptionRemote-first culture with home office supportComprehensive health benefits (Medical, Dental, Vision, HSA)401(k) plan and life insuranceFlexible time off and 12 weeks parental leaveProfessional development reimbursementOur Ideal Teammate:Thrives in a fast-paced startup and is comfortable navigating ambiguityExcited to wear multiple hats and grow rapidlyCommitted to our mission of saving lives through technology
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