Senior AI/ML Performance Engineer

Performance Optimization:Conduct deep-dive analyses of production workloads toidentifybottlenecks and propose high-impact optimization strategies.

Cross-Functional Collaboration:Partner with AI/ML Research, Infrastructure Engineering, and Cloud Vendors to spearhead projects that enhance engineering velocity and cost-efficiency.

Proactive System Scaling:Identifyopportunities for architectural improvements to ensure the scalability and reliability of large-scale ML training and inference environments.

Yourskills &abilities (Required Qualifications)

Experience:5+ years of professional experience in high-scale infrastructure or ML systems.

Education:Bachelor’s Degree in Computer Science, a related technical field, or equivalent practical experience.

Software Proficiency:Expert-level coding skills inPythonand the ability to architect/debug within thePyTorchecosystem.

Systems Engineering:Proventrack recordof resolving performance issues within large-scale distributed production environments.

Architectural Knowledge:Deep understanding of distributed systems, specifically modern ML system design and high-performance computing (HPC).

Containerization:Hands-on experience withKubernetesfor orchestrating complex workloads.

GPU Monitoring:TechnicalproficiencywithNvidia DCGM,nvidia-smi, andGrafanafor real-time telemetry and observability.

Cloud Platforms:Extensive experience working within major cloud ecosystems (AWS, GCP, or Azure).

Whatwillgiveyouacompetitiveedge (Preferred Qualifications)

Advanced Experience:8+ years of relevant industry experience.

Hardware Expertise:Working knowledge of Enterprise-grade Nvidia GPU architectures, includingH100, B200, and GB200.

Model Deployment:Experience deploying and scaling open-source models via theHugging Faceecosystem.

Data Analytics:ProficiencyinBigQueryfor large-scale data analysis and reporting.

Profiling Tools:Practical experience utilizingNvidia NsightandNsight Computefor kernel-level performance tuning.

Soft Skills:Strong technical communication skills with the ability to translate complex infrastructure needs into actionable business insights.

Hybrid:This role is categorized as Hybrid. This means the successful candidate is expected to report toSunnyvale Technical Centeratminimumthree days per week or at the hiringmanager’sdiscretion. Ability to sit remote in Seattle, WA until office opens.

Compensation:The compensation information is a good faith estimate only. It is based on what a successful applicant might be paidin accordance withapplicable state laws. The compensation may not be representative for positionslocatedoutside of New York, Colorado, California, or Washington.

The salary range for this role:is $144,700 to $261,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

Bonus Potential:An incentivepayprogram offers payouts based on company performance, job level, and individual performance.

Benefits:GM offers a variety of health and wellbeing benefit programs.Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuitionassistanceprograms, employeeassistanceprogram, GM vehicle discounts and more.







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