Staff Machine Learning Engineer
Location: Redwood City CA
Hybrid 2 days onsite in a weeek
Salary $150-250K
Required Qualifications:
-
Bachelors degree or higher in Computer Science or a related field.
-
At least 7 years of professional experience in the software industry with a minimum of 2 years in a tech lead role.
-
Proven experience with high-performance computing environments and distributed systems.
-
Demonstrated ability to scale ML training systems and optimize resource utilization.
-
Hands-on experience with job scheduling systems and managing cloud GPU environments (GCP AWS etc.).
-
Deep understanding of distributed computing concepts including race conditions memory optimization and parallel processing.
-
Hands-on experience in ML model tuning for performance.
-
Experience with common ML training and inference tools including PyTorch TensorRT Triton Accelerate etc.
-
Strong analytical and problem-solving skills with the ability to troubleshoot complex system issues.
-
Excellent communication skills to collaborate effectively with cross-functional teams.
Preferred Qualifications:
Staff Machine Learning Engineer Location: Redwood City CA Hybrid 2 days onsite in a weeek Salary $150-250K Required Qualifications: Bachelors degree or higher in Computer Science or a related field. At least 7 years of professional experience in the software industry with a minimum of 2...
Staff Machine Learning Engineer
Location: Redwood City CA
Hybrid 2 days onsite in a weeek
Salary $150-250K
Required Qualifications:
-
Bachelors degree or higher in Computer Science or a related field.
-
At least 7 years of professional experience in the software industry with a minimum of 2 years in a tech lead role.
-
Proven experience with high-performance computing environments and distributed systems.
-
Demonstrated ability to scale ML training systems and optimize resource utilization.
-
Hands-on experience with job scheduling systems and managing cloud GPU environments (GCP AWS etc.).
-
Deep understanding of distributed computing concepts including race conditions memory optimization and parallel processing.
-
Hands-on experience in ML model tuning for performance.
-
Experience with common ML training and inference tools including PyTorch TensorRT Triton Accelerate etc.
-
Strong analytical and problem-solving skills with the ability to troubleshoot complex system issues.
-
Excellent communication skills to collaborate effectively with cross-functional teams.
Preferred Qualifications:
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