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Crystal Equation
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Pay range is $71 - $76 per hour with full benefits available, including paid time off, medical/dental/vision/life insurance, 401K, parental leave, and more. Our compensation reflects the cost of labor across several US geographic markets. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.
THE PROMISES WE MAKE:
At Crystal Equation, we empower people and advance technology initiatives by building trust. Your recruiter will prep you for the interview, obtain feedback, guide you through any necessary paperwork and provide everything you need for a successful start. We will serve to empower you along the way and provide the path for your professional journey.
Machine Learning Infrastructure Engineer
Summary:
Our Sensors Team is helping build novel products in Augmented and Virtual Reality. Our AR/VR research and development in Sensors and Sensing Systems is driving the state-of-the-art forward through relentless innovation. Our team explores, develops, and delivers new cutting-edge technologies that serve as the foundation of current and future AR/VR products at our company. We are looking for candidates with experience in software engineering with a deep understanding of software infrastructure and machine learning (ML) systems. This role will focus on designing and implementing systems to support ML development for sensor systems.
Responsibilities:
Minimum Qualifications:
Preferred Qualifications:
Machine Learning Infrastructure Engineer
1180 Discovery Way Sunnyvale, CA 94089 US
Posted: 01/12/2024
2024-01-12
2024-04-06
Job Number: 38509
Job Description
Pay range is $71 - $76 per hour with full benefits available, including paid time off, medical/dental/vision/life insurance, 401K, parental leave, and more. Our compensation reflects the cost of labor across several US geographic markets. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.
THE PROMISES WE MAKE:
At Crystal Equation, we empower people and advance technology initiatives by building trust. Your recruiter will prep you for the interview, obtain feedback, guide you through any necessary paperwork and provide everything you need for a successful start. We will serve to empower you along the way and provide the path for your professional journey.
Machine Learning Infrastructure Engineer
Summary:
Our Sensors Team is helping build novel products in Augmented and Virtual Reality. Our AR/VR research and development in Sensors and Sensing Systems is driving the state-of-the-art forward through relentless innovation. Our team explores, develops, and delivers new cutting-edge technologies that serve as the foundation of current and future AR/VR products at our company. We are looking for candidates with experience in software engineering with a deep understanding of software infrastructure and machine learning (ML) systems. This role will focus on designing and implementing systems to support ML development for sensor systems.
Responsibilities:
- Design and develop systems to support Machine Learning algorithm development within the team.
- Own the system design that will cater to multi-modal input, quick prototyping of algorithms, visualization tools and state-of-the-art ML algorithm architecture development.
- Build distributed systems and pipelines for data management, ensuring scalability, reliability and performance.
- Demonstrate a deep understanding of DevOps practices and apply them to ML operations.
- Handle the complexities of designing and implementing ML infrastructure systems in a dynamic and fast-paced environment.
- Contribute to the overall impact of the team by delivering robust and efficient ML infrastructure.
Minimum Qualifications:
- Bachelor's degree in Computer Science or a related field.
- Minimum 5+ years of experience in software engineering, with a focus on infrastructure design.
- 5+ years experience in Python and C++.
- Proven experience in designing complex systems and strong software engineering skills.
- Strong understanding and experience with distributed systems and infrastructure design.
- Demonstrated expertise in DevOps practices, with a focus on ML.
Preferred Qualifications:
- Experience with ML pipeline automation and data management in ML workflows.
- Previous experience building ML systems and working on ML adjacent teams.
- Demonstrated experience in cross-group and cross-culture collaboration.
- Familiarity with the emerging Augmented Reality and Virtual Reality technologies.
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