Lead LLM inference optimization for Qualcomm Cloud AI accelerators, working with customers and internal teams to deploy and tune generative AI workloads.
Responsibilities
Deploy and optimize LLM and multimodal inference workloads on Qualcomm Cloud AI accelerator platforms
Profile and optimize prefill and decode performance metrics
Analyze model architecture and runtime bottlenecks across compute, accelerator memory, host memory, KV cache, interconnect, networking, and software stack
Optimize model execution using quantization, batching, continuous/dynamic batching, KV-cache management, paged attention, prompt/context-length tuning, and speculative decoding
Optimize distributed inference across tensor, pipeline, data, context, and expert parallelism
Requirements
Master’s degree or higher in Computer Science, Electrical/Computer Engineering, AI/ML, or related technical field
Lead on-device AI inference and systems for Unity’s game engine, driving performance, optimization, and integration of generative models across mobile, desktop, and web platforms.
Compensation
Base Salary Range: We determine the base salary range for this role based on your primary work location:
Zone A: $250,300 - $325,400
Zone B: $222,600 - $289,400
Zone C: $197,400 - $256,600
Responsibilities
Own end-to-end optimization pipeline for on-device AI models
Design and implement runtime integration between ML inference and game engine
Lead a team of senior and mid-level engineers
Set engineering standards and KPIs for latency, memory, and power
Collaborate with research scientists to productionize novel architectures
Computer Vision Algorithm Engineer focused on ADAS perception, developing and optimizing image processing and deep learning models for automotive embedded systems.
Responsibilities
Design, implement, and optimize conventional image processing algorithms for automotive embedded serial production projects
Develop and tune deep learning models for ADAS computer vision features, including pruning and quantization
Plan and execute experiments to assess deep learning model effectiveness and validate results
Analyze large datasets to extract insights and improve model performance
Collaborate with multidisciplinary teams to integrate models into existing systems
Requirements
Master’s degree in computer engineering, Software Engineering, Electrical Engineering, Computer Science, or equivalent
Nice to have: experience in serial development of automotive electronics
Seeking a Sr. Staff Engineer to design and architect enterprise-wide Generative AI solutions, build AI gateways, and lead a team of AI/ML engineers.
Compensation
Base Pay Range 225,000.00
Responsibilities
Design and architect enterprise-wide Generative AI solutions, including reference architectures, integration patterns, and technical standards.
Design, build, and maintain an enterprise AI gateway to centralize access, governance, and monitoring of AI model consumption across the organization.
Develop and implement intelligent routing techniques to direct requests across multiple large language models (LLMs) and AI providers based on cost, latency, accuracy, and availability requirements.
Evaluate and integrate local/on-premises models as alternatives to third-party hosted models, with a focus on reducing operational costs.
Establish frameworks for measuring and demonstrating cost savings achieved through model selection, routing optimization, and infrastructure decisions.
Design, build, and deploy LLM-powered tools that support software development activities such as code generation, code review, debugging, refactoring, automated test creation, and documentation.
Compensation
The base pay range for this position is $130,000.00-$173,000.00 USD Annually. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary/ commission based on the plan.
Responsibilities
Design, build, and deploy LLM-powered tools that support software development activities such as code generation, code review, debugging, refactoring, automated test creation, and documentation.
Develop retrieval-augmented generation (RAG) pipelines that ground model outputs in internal engineering artifacts including codebases, requirements, design documentation, standards, and domain knowledge.
Create agentic workflows that interact with engineering toolchains such as compilers, static analyzers, test frameworks, version control systems, and issue-tracking platforms.
Evaluate and select models based on performance, cost, latency, licensing, and security requirements.
Apply techniques such as prompt engineering, fine-tuning, and parameter-efficient adaptation to improve model usefulness for aerospace and embedded software use cases.
Requirements
Bachelor’s degree in Computer Science, Software Engineering, or related STEM field.
Nice to have: Master’s degree in Computer Science, Machine Learning, or related field.
Lead inference performance for Runware’s AI Factory, owning kernel development, benchmarking, and team leadership across GPU, HPC, and deep learning systems.
Responsibilities
Own inference performance end to end for the fleet
Set the model performance roadmap
Write and tune CUDA kernels, fuse attention and MLP paths
Build pipelines for new model deployment
Choose and shape the serving stack
Requirements
Nice to have: Diffusion and video generation performance
Data Center LLM Optimization Customer EngineerNewQualcomm · Shanghai, China
Senior AI/ML Engineer - Generative AI for Software DevelopmentGE Aerospace · Grand Rapids, US
Developer AdvocateWafer · San Francisco, US