Staff Machine Learning Engineer
14 hours ago
Our Engineering team built the world's largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 15 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy.
We're looking for an experienced Staff Machine Learning Engineer to join our Shared Platform Services. Reporting to the Director, Engineering; you'll be responsible for:
- Architecting, building and maintaining robust, large-scale distributed systems to support the entire ML pipeline on the client side, including data collection, feature engineering, model training, model evaluation, model deployment, and real-time serving
- Developing functional specifications, assess task requirements and scheduling, and actively participate in the development, debugging, and support of client-side ML solutions
- Solving complex real-world business problems by working closely with various stakeholders, including data scientists, product management, and product engineering teams
- Developing implement, and optimize C/C++ code for the efficient execution of machine learning models on client side or server side depending on the use case
- Integrating and running various machine learning models on client platforms, ensuring optimal performance and resource utilization
- 8+ years of experience as a Software Engineer including 3+ years of ML platform engineer, with a focus on client-side development.
- Experience in C/C++ programming for high-performance applications
- Good understanding of Windows OS and experience building applications on Windows OS using Visual Studio
- Strong experience with algorithms and programming skills in building out data collection/processing infrastructure, Machine Learning model training, and serving platforms on client devices
- Experience with SLM models and running different ML models on client-side environments
- Strong experience with LLMs, agent architectures and prompt engineering
- Experience with ONNX runtime for optimizing and deploying machine learning models
- Advanced degree or certifications in Machine Learning
#LI-GL2
#LI-Hybrid
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