обновлено 6 дней назад
AI Inference Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Inference Engineer (AI/C++): Deploying and optimizing machine learning inference pipelines for edge devices with an accent on modern C++, AI model integration, memory usage, and latency. Focus on profiling production inference, integrating LLM and deep learning architectures, and transitioning models from research environments into existing products.
Location: Ukraine; remote flexibility is offered
Company
is an AI engineering company building production systems for companies including Procter & Gamble and Shutterstock.
What you will do
- Deploy machine learning models to edge devices using llama.cpp and ggml.
- Integrate, evaluate, profile, and optimize AI inference pipelines for high-performance on-device execution.
- Collaborate with researchers on coding, training, and transitioning models from research to production.
- Integrate AI features into existing products using modern machine learning advancements.
Requirements
- 4+ years of professional experience with Modern C++17/20.
- Strong knowledge of memory management, multithreading, profiling, performance optimization, and low-level debugging.
- Experience developing in Linux environments and integrating machine learning models into production applications.
- Experience deploying and optimizing inference pipelines and profiling memory usage and latency.
- Understanding of Transformer architecture, LLMs, diffusion models, tokenization, attention mechanisms, KV cache, quantization, model conversion, and deployment.
- Practical experience with LLM deployment, computer vision, OCR, multimodal, speech, or image generation models.
Nice to have
- Experience with llama.cpp, ggml, ONNX Runtime, TensorRT, TensorRT-LLM, OpenVINO, MLC LLM, ExecuTorch, or TVM.
- CUDA, Vulkan Compute, Metal, OpenCL, TypeScript, or Python.
- Experience contributing to open-source AI infrastructure projects.
- Experience evaluating new models and integrating them into existing products.
Culture & Benefits
- Remote work flexibility.
- Competitive compensation with medical, wellness, and learning benefits.
- English classes, professional development, well-being support, and career progression opportunities.
- Ownership of problem-solving initiatives and support for responsible experimentation.
- Regular meetups, tech talks, and collaborative support from colleagues.
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