Senior Embedded Engineer

Senior Embedded Engineer
Warszawa
NR REF.: 1187321


Your new company
For our Client - global technology and analytics services company, we are currently looking for a person interested in the position of a Senior Embedded Engineer.

Your new role

• Develop and optimise AI inference models for deployment on edge devices with embedded GPU/TPU accelerators, focusing on local LLM inference.
• Influence the Edge AI strategy by providing expert advice on design and architecture.
• Implement and fine-tune low-latency model inference pipelines to meet real-time performance requirements.
• Collaborate with the GPU Hardware Design Team to design and optimise GPUs that power next-generation devices.
• Conduct performance profiling and optimisation to maximise 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.
• Collaborate with cross-functional teams to integrate AI inference solutions into edge computing platforms and applications.
• Make critical decisions regarding technical directions, scalability, and system performance.
• Provide technical expertise and support to project teams, ensuring successful implementation and deployment of edge AI solutions.

What you39ll need to succeed
We’re seeking a Senior Embedded Engineer with expertise in Edge AI to join our clients39 team. As a key contributor, you’ll shape the future of Edge AI solutions. Combine technical excellence with effective leadership to drive projects forward with hands-on experience with Large Language Models inference using embedded GPU/TPU architectures. 

• 5+ years of experience in AI model development and deployment, with a focus on edge computing.
• Competence in LLM frameworks (e.g., vLLM, Text generation inference, OpenLLM, Ray Serve, and HuggingFace Transformers) and deep learning libraries.
• Experience with GPU/TPU acceleration for AI inference, including optimisation techniques (tensor, pipeline, data, sharded data parallelism) and performance tuning.
• Programming skills in languages such as Python and C++.
• Familiarity with one or more GPU frameworks: CUDA, Vulkan, OpenCL, familiarity with NVIDIA Jetson, ARM Mali, or relevant SoC configurations.
• Knowledge of parallel computation, memory scheduling, and structural optimisation.

What39s in it for You?

• Remote work
• Medical subscription
• Free unlimited access to Udemy – 5 days off yearly to enjoy courses
• Paid study holiday for bachelor students
• Referral bonus
• Long-term contribution rewards
• Lunch & Learn sessions
• Company sports competitions, hackathons, reading marathons
• Social community events
• Team building parties, team events

What you need to do now 
If you39re interested in this role, click 39apply now39 to forward an up-to-date copy of your CV, or call us now. 


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