Senior Manager, AI Deployment

🕒 vor 18 Tagen

🏄 California – Remote

🏄 California – Remote

💵 $296.300 - $453.900 / Jahr

⏰ Vollzeit

🟠 Senior

🤖 Künstliche Intelligenz

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

👻 Geisterscore 0%

Was es bedeutet: wie wahrscheinlich diese Stelle offen bleibt, ohne dass aktiv eingestellt wird.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Wie wir werten: Dauer offen, Neuveröffentlichungen, offene Stellen vs Teamgröße, wie schnell Stellen geschlossen werden, und ob ein Gehalt angegeben ist.Hinweis: eine Schätzung aus öffentlichen Daten, kein Urteil über das Unternehmen. Echte Stellen können hoch punkten, nutze es also als Hinweis, nicht als Fakt.

Jetzt Bewerben

Ähnliche Remote-Jobs finden

E-Mail-Benachrichtigung für neue Jobs einrichten

📊 Überprüfen Sie Ihre Lebenslauf-Bewertung für diese Stelle

Verbessern Sie Ihre Chancen auf ein Vorstellungsgespräch, indem Sie Ihre Lebenslauf-Bewertung vor der Bewerbung überprüfen.

Lebenslauf hochladen

General Motors

WebsiteLinkedInAlle Stellen

10.000+ Mitarbeiter

Gegründet 1908

🚘 Automobilindustrie

🏭 Fertigung

🚗 Transport

💰 €500.000.000 Grant im 2024-07

Automotive • Manufacturing • Transport

General Motors ist ein führendes multinationales Unternehmen in der Automobilbranche und engagiert sich für eine Zukunft ohne Unfälle, ohne Emissionen und ohne Staus. Mit weltweiten Betrieben und Einrichtungen konzentriert sich GM auf Innovation in verschiedenen Bereichen, einschließlich Ingenieurwesen, Fertigung und Informationstechnologie. Das Unternehmen legt Wert auf Vielfalt, Inklusion und die Entwicklung nachhaltiger Technologien, um die Zukunft der Mobilität zu gestalten.

Beschreibung

• Lead the strategy, roadmap, and operating plan for AI model performance and inference quality • Establish performance budgets for latency, throughput, memory, GPU utilization, power, and numerical parity • Lead investigations into performance bottlenecks across model architecture, operators, kernels, memory movement, scheduling, runtime behavior, and hardware utilization • Establish repeatable benchmarking and profiling practices across simulation, hardware-in-the-loop, bench, and vehicle environments • Guide optimization through model architecture changes, operator and kernel improvements, memory optimization, scheduling, and hardware-aware execution • Build performance dashboards, regression detection, benchmark automation, and root-cause diagnostics • Partner with Embodied AI, model development, GPU kernel, runtime, system performance, vehicle integration, simulation, and safety teams • Translate profiling results into recommendations for model architects and researchers • Represent AI Deployment in architecture reviews, program planning, and senior leadership discussions • Build and lead an inclusive, high-performing organization through hiring, coaching, feedback, and manager development • Establish ownership, priorities, staffing plans, and operating rhythms across performance workstreams • Define and manage KPIs for inference latency, latency variability, throughput, memory efficiency, GPU utilization, parity, and regression rate • Balance near-term production needs with longer-term investments in profiling, optimization automation, reduced precision, and performance infrastructure • Resolve cross-functional issues and align stakeholders on performance, quality, and implementation trade-offs • Develop technical leaders and succession plans in GPU performance, model optimization, inference systems, and numerical analysis

🎯 Anforderungen

• Bachelor’s degree in Computer Science, Electrical or Computer Engineering, Robotics, Machine Learning, or a related field; advanced degree preferred, or equivalent experience • 10+ years of experience in machine learning systems, model optimization, inference, GPU systems, robotics, autonomous driving, or a related field • 5+ years of people-leadership experience, including leading managers or senior technical leaders • Experience shipping production machine-learning inference systems on GPU, accelerator, robotics, automotive, or other edge hardware • Strong understanding of model-performance factors including architecture, tensor shapes, operators, kernels, memory movement, scheduling, runtime execution, and hardware utilization • Hands-on experience with several of PyTorch, CUDA, C++, Python, TensorRT, GPU profiling, benchmarking, performance analysis, or inference runtimes • Experience with quantization, pruning, distillation, architecture optimization, kernel optimization, or memory optimization • Experience building benchmark automation, performance regression detection, telemetry, dashboards, or profiling workflows • Strong systems thinking, communication, decision-making, and cross-functional leadership skills • Experience optimizing real-time machine-learning systems for autonomous driving, robotics, embedded systems, or computer vision • Experience with GPU performance, memory bandwidth, occupancy, synchronization, stream scheduling, or device-to-device data movement • Experience with NVIDIA Nsight Systems, NVIDIA Nsight Compute, PyTorch Profiler, TensorRT profiling tools, or equivalent tools • Experience deploying reduced-precision models and managing calibration, sensitivity, parity, and model-quality risks • Experience optimizing transformer, vision, lidar, or multimodal workloads • Experience measuring performance across simulation, hardware-in-the-loop, bench, and vehicle environments • Experience with safety-critical or highly reliable systems

🏖️ Vorteile

• Bonus potential through an incentive pay program based on company performance, job level, and individual performance • Medical, dental, and vision benefits • Health Savings Account • Flexible Spending Accounts • Retirement savings plan • Sickness and accident benefits • Life insurance • Paid vacation and holidays • Remote work with no expected reporting to a GM worksite unless directed by the manager • Travel under 25% • Potential eligibility for relocation benefits