Senior Embedded Engineer

3 dni temu

Warsaw, Polska R Systems Pełny etat

technologies-expected :
Python
C++

about-project :
We are seeking a talented Edge AI Engineer with specialized expertise in GPU/TPU acceleration to join our team. The ideal candidate will have extensive hands-on experience in local Large Language Models (LLM) inference with embedded GPU/TPU architectures. As Principal Engineer specializing in Edge AI, you will play a crucial role in shaping the future Edge AI solution, leveraging the power of GPU/TPU acceleration and enterprise grade, large scale edge compute.
The successful candidate will combine technical excellence with effective leadership, creating a positive impact on both projects and team dynamics.

responsibilities :
Influence the Edge AI strategy by providing expert advice on design and architecture
Make critical decisions regarding technical directions, scalability, and system performance
Develop and optimize AI inference models for deployment on edge devices with embedded GPU/TPU accelerators, focusing on local Low Latency Model (LLM) inference
Implement and fine-tune low-latency model inference pipelines to meet real-time performance requirements
Collaborate with cross-functional teams to integrate AI inference solutions into edge computing platforms and applications
Collaborate with the GPU Hardware Design Team to design and optimize GPUs that power next-generation devices
Conduct performance profiling and optimization to maximize the efficiency of GPU/TPU acceleration for local LLM inference
Work on micro-architecture development, ensuring efficient execution of graphics, compute, and AI workloads within energy and area constraints
Stay current with advancements in GPU/TPU technologies and edge AI frameworks, incorporating them into solution designs as appropriate
Provide technical expertise and support to project teams, ensuring successful implementation and deployment of edge AI solutions
Lead and inspire a team of engineers, providing guidance, setting goals, and ensuring collaboration
Oversee project planning, execution, and delivery, ensuring alignment with business objectives
Manage all phases of technical projects, from conception to completion
Develop project specifications, track progress, and control costs
Foster a positive work environment, encouraging professional growth and knowledge sharing

requirements-expected :
Bachelor’s degree in computer science, Engineering, or a related field; Master’s degree preferred
5+ years of hands-on experience in AI model development and deployment, with a focus on edge computing and local LLM inference
Strong programming skills in languages such as Python and C++
Proficiency in LLM frameworks (e.g., vLLM, Text generation inference, OpenLLM, Ray Serve, and HuggingFace Transformers) and deep learning libraries
Extensive experience with GPU/TPU acceleration for AI inference, including optimization techniques (tensor, pipeline, data, sharded data parallelism) and performance tuning,
Hands on experience with one or more GPU frameworks: CUDA, Vulkan, OpenCL
Deep knowledge of GPU memory layout, familiarity with NVIDIA Jatison, ARM Mali or relevant SoC configurations
Knowledge of parallel computation, memory scheduling, and structural optimization
Excellent problem-solving and analytical skills, with a passion for innovation and continuous learning

offered :
More free time to enjoy throughout the year: longer holidays than standard, 5 free days/year for professional training, paid study holidays, flexible working schedule and so much more
Private medical subscription for you and family members
Customized training and professional certifications programs to achieve your learning and career goals
Free and unlimited access to Udemy online learning platform, to learn all and everything from programming and cloud computing to home gardening 101
Mobile device and mobile subscription plan
Cool and comfy office located right in the heart of the city
Lunch & Learn sessions
(Inter)company sports competitions
Team buildings and parties

benefits :
sharing the costs of sports activities
private medical care
remote work opportunities
flexible working time
integration events
mobile phone available for private use
no dress code
video games at work
coffee / tea
parking space for employees
leisure zone

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