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Operations engineer • fremont ca
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Operations & Maintenance Engineer.Position is located onsite in Pleasanton, TX, candidate must live in close proximity or be willing to relocate.
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Staff Software Engineer - Machine Learning Platform
Pony.aiFremont, California, United Statesjob_description.job_card.30_days_ago
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job_description.job_card.job_descriptionExperience in building the infrastructure for large language or vision models Experience building and architecting large-scale, production quality backend systems, especially in applied machine learning or data pipeline Familiar with parallel / distributed systems Experiences in tech leading a team to launch projects Health Care Plan (Medical, Dental & Vision) Retirement Plan (Traditional and Roth 401k) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Free Food & Snacks
Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous mobility and is a pioneer in extending autonomous mobility technologies and services at a rapidly expanding footprint of sites around the world. Operating Robotaxi, Robotruck and Personally Owned Vehicles (POV) business units, Pony.ai is an industry leader in the commercialization of autonomous driving and is committed to developing the safest autonomous driving capabilities on a global scale. Pony.ai’s leading position has been recognized, with CNBC ranking Pony.ai #10 on its CNBC Disruptor list of the 50 most innovative and disruptive tech companies of 2022. In June 2023, Pony.ai was recognized on the XPRIZE and Bessemer Venture Partners inaugural “XB100” 2023 list of the world’s top 100 private deep tech companies, ranking #12 globally. As of August 2023, Pony.ai has accumulated nearly 15 million miles of autonomous driving globally.
Responsibility
- Lead the development, optimization and productionization of the machine learning platform
- Improve the scalability and efficiency of the training infrastructure that enable a fast research to production lifecycle
- Provide tooling to help ML practitioners evaluate, debug, and improve ML algorithms, data and hyperparameters
- Develop efficient model deployment frameworks that can put large deep learning models on the compute with limited GPU resources on the vehicle
- Collaborate with and support other teams, including perception, planning and data, to facilitate their model developments and deployments
- BS, MS or PhD in Computer Science, similar technical field of study, or equivalent practical experience
- Experience building full ML model lifecycle solutions - from feature engineering to training, validation, deployment and monitoring.
- Extensive experience programming in Python or C++.
- Extensive hands-on deep learning experiences
- Extensive hands-on experiences in building deep learning infrastructure
- Experience with machine learning compiler / runtime or GPU accelerator
- Passionate in autonomous driving
Preferred Experience
Compensation and Benefits
Base Salary Range : $220,000 - $285,000 Annually
Compensation may vary outside of this range depending on many factors, including the candidate’s qualifications, skills, competencies, experience, and location. Base pay is one part of the Total Compensation and this role may be eligible for bonuses / incentives and restricted stock units.
Also, we provide the following benefits to the eligible employees :