Signify Technology
Machine Learning System Engineer
Signify Technology, San Jose, California, United States, 95199
Overview
Job Title:
Machine Learning System Engineer Salary:
$300K - $500K + Equity Location:
Bay Area, CA An AI startup is seeking a Senior Systems Engineer to optimize deep learning performance at scale. In this role, you’ll work at the intersection of systems, infrastructure, and machine learning, driving improvements across model training, inference, and distributed compute environments. You’ll focus on kernel-level optimization, GPU/accelerator efficiency, and deep framework tuning to push the boundaries of performance for next-generation AI workloads. You’ll wear multiple hats in a startup environment and contribute across large-scale data processing, model parallelism, and runtime efficiency. The role requires expertise in CUDA/Triton, PyTorch internals, and distributed training systems, with the ability to diagnose and optimize performance bottlenecks across kernels, frameworks, and clusters. If you thrive on accelerating training and inference performance at scale, this is a chance to make a major impact.
Responsibilities
Optimize deep learning performance at scale, focusing on kernel-level optimization, GPU/accelerator efficiency, and deep framework tuning. Work at the intersection of systems, infrastructure, and machine learning to drive improvements across model training, inference, and distributed compute environments. Diagnose and optimize performance bottlenecks across kernels, frameworks, and clusters; contribute across large-scale data processing and runtime efficiency.
Qualifications
3+ years of systems-level engineering experience in deep learning environments Strong Python development and debugging skills Kernel optimization (parallelization, performance tuning) GPU / AI accelerator compute model familiarity Large-scale distributed training (diagnosing bottlenecks in clusters) PyTorch framework optimization and runtime improvements Deep understanding of CUDA, Triton, and related internals
Benefits
Health, Dental, and Vision Insurance Paid Time Off and Parental Leave 401k Work in a collaborative high-impact environment
Accessibility and Diversity Statements
Accessibility Statement: Read and apply for this role in the way that works for you by using our assistive technology tool. Please let us know if you require any accessibility adjustments through the application or interview process. Our Commitment to Diversity, Equity, and Inclusion: Our mission is to empower every person, regardless of their background or circumstances, with an equitable chance to achieve the careers they deserve.
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Job Title:
Machine Learning System Engineer Salary:
$300K - $500K + Equity Location:
Bay Area, CA An AI startup is seeking a Senior Systems Engineer to optimize deep learning performance at scale. In this role, you’ll work at the intersection of systems, infrastructure, and machine learning, driving improvements across model training, inference, and distributed compute environments. You’ll focus on kernel-level optimization, GPU/accelerator efficiency, and deep framework tuning to push the boundaries of performance for next-generation AI workloads. You’ll wear multiple hats in a startup environment and contribute across large-scale data processing, model parallelism, and runtime efficiency. The role requires expertise in CUDA/Triton, PyTorch internals, and distributed training systems, with the ability to diagnose and optimize performance bottlenecks across kernels, frameworks, and clusters. If you thrive on accelerating training and inference performance at scale, this is a chance to make a major impact.
Responsibilities
Optimize deep learning performance at scale, focusing on kernel-level optimization, GPU/accelerator efficiency, and deep framework tuning. Work at the intersection of systems, infrastructure, and machine learning to drive improvements across model training, inference, and distributed compute environments. Diagnose and optimize performance bottlenecks across kernels, frameworks, and clusters; contribute across large-scale data processing and runtime efficiency.
Qualifications
3+ years of systems-level engineering experience in deep learning environments Strong Python development and debugging skills Kernel optimization (parallelization, performance tuning) GPU / AI accelerator compute model familiarity Large-scale distributed training (diagnosing bottlenecks in clusters) PyTorch framework optimization and runtime improvements Deep understanding of CUDA, Triton, and related internals
Benefits
Health, Dental, and Vision Insurance Paid Time Off and Parental Leave 401k Work in a collaborative high-impact environment
Accessibility and Diversity Statements
Accessibility Statement: Read and apply for this role in the way that works for you by using our assistive technology tool. Please let us know if you require any accessibility adjustments through the application or interview process. Our Commitment to Diversity, Equity, and Inclusion: Our mission is to empower every person, regardless of their background or circumstances, with an equitable chance to achieve the careers they deserve.
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