Lead Software Engineer - Backend Platform jobs at Jpmorgan in United States, Palo Alto
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Job type
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United States
State
Palo Alto
55 jobs found
24.12.2024
JPM
JPMorgan Applied AI ML Director Machine Learning Platform United States, California, Palo Alto
Achieve state-of-the-art throughput for critical models using advanced techniques like model parallelism and distributed training. Reduce inference time for new model architectures using optimizations like quantization and pruning. Collaborate closely...
Develop, Implement and maintain security features in backend systems, including authentication, authorization, encryption and access controls. Create secure and high-quality production code and maintains algorithms that run synchronously with appropriate...
Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems. Creates secure and high-quality production...
Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors. Develops secure and high-quality production code, and reviews and debugs code written by...
Manage and build relationships with clients by earning trust, thoroughly understanding client needs, providing targeted advice, developing thoughtful solutions and delivering an exceptional client experience. Generate business results and acquire...
Assess existing cryptographic libraries. Evaluate existing crypto-agile approaches and tools - help define and implement JPMC-centric solutions. Define and develop tools or libraries for cryptography services. Review architecture document for...
Executes basic software solutions, design, development, and technical troubleshooting. Writes secure and high-quality code using the syntax of at least one programming language with peer guidance. Interprets architecture and design...
Achieve state-of-the-art throughput for critical models using advanced techniques like model parallelism and distributed training. Reduce inference time for new model architectures using optimizations like quantization and pruning. Collaborate closely...
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