Edge AI Machine Learning Engineer - Romania Location
Răspunde la anunț- on experience in developing and optimizing AI inference models for embedded GPU/NPU architectures. As a Principal Machine Learning Engineer specializing in Edge AI, you will play a crucial role in shaping the future Edge AI solution, leveraging the power of GPU/NPU acceleration and
- grade,
- scale edge computing. You will combine technical excellence with effective leadership, creating a positive impact on both projects and team dynamics.
- 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/NPU accelerators, focusing on
- latency inference runtimes. - Implement and
- tune
- latency inference pipelines to meet
- time performance requirements. - Collaborate with
- 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/NPUs that power
- generation devices. - Conduct performance profiling and optimization to maximize the efficiency of GPU/NPU acceleration for Edge AI inference.
- Work on
- architecture development, ensuring efficient execution of graphics, compute, and AI workloads within energy and area constraints. - Stay current with advancements in GPU, NPU, 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.
- Bachelor’s degree in computer science, Engineering, or a related field; Master’s degree preferred.
- 5+ years of
- on experience in AI model development and deployment, with a focus on edge computing and inference runtime optimization. - Strong programming skills in languages such as Python and C/C++
- Proficiency in ML frameworks (e. g. , Scikit-learn, Tensor
Flow, Py
Torch, XGBoost) with focus on edge AI applications deployment (e. g. , Glow, TFLite, Tensor
RT) - Experience with MLOps frameworks (e. g. , Kubeflow, MLflow, TFX, Airflow, H2O)
- Extensive experience with GPU/NPU acceleration for AI inference, including optimization techniques (tensor, pipeline, data, sharded data parallelism) and performance tuning,
- Hands on experience with one or more GPU/NPU frameworks: CUDA, Vulkan, Open
CL, familiarity with NVIDIA Jetson, ARM Mali, or relevant So
C configurations. - Knowledge of parallel computation, memory scheduling, and structural optimization
- Excellent
- solving and analytical skills, with a passion for innovation and continuous learning.
- Experience with edge device hardware and software integration.
- Familiarity with edge computing architectures and Io
T platforms. - Experience with edge AI applications in domains such as robotics, autonomous vehicles, or industrial automation
About R Systems:
WE SPEAK DIGITAL. Overview
Formerly known as Computaris, we are the European branch of R Systems - global technology and analytics services company. We help our clients achieve
-
- market, overcome digital barriers, and create business value with our specialized service offerings and consultative business approach. We speak the language of business as fluently as we do the language of technology. In other words: We speak Digital. Our goal: accelerate our clients’ digital leadership. Our clients choose to partner with us for Cloud transformation, automation, data science, analytics, and product engineering, thanks to our technical expertise, domain knowledge, global presence and a record of delivering
- class solutions consistently for over 28 years. With a global workforce of 4, 800+ employees spread across 16
- centers and 26 offices, we continue to empower organizations with
- edge technologies. In Europe, R Systems has offices in the UK, Romania, Poland, Moldova and Switzerland, providing digital transformation services and extensive telecom expertise.
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