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ОБЩЕСТВО С ОГРАНИЧЕННОЙ ОТВЕТСТВЕННОСТЬЮ "ЦЕНТР НАЦИОНАЛЬНЫХ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ" ИНН: 9704271170
описание
The team is building an AI agent that takes on everyday users’ tasks, including running errands, managing workflows, and maintaining context across long, complex conversations.
задачи
Build end-to-end pipelines across data, training, evaluation, and inference
Adapt and fine-tune models using LoRA, QLoRA, SFT, DPO, and distillation
Architect inference systems that meet real-world latency and cost constraints
Create data pipelines for high-quality synthetic and real-world training data
Evaluate robustness, safety, bias, and production behaviour beyond benchmarks
Own deployment, including GPU optimisation, quantisation, memory efficiency, and scaling
Work with application engineers to integrate ML into backend, mobile, and desktop products
Take ideas from research into scalable, reliable production systems that improve over time
требования
Deep understanding of deep learning and transformer architectures
Proven experience training, fine-tuning, or shipping large-scale models in production
Strong skills in at least one major ML framework, such as PyTorch or JAX, and ability to learn others quickly
Familiarity with distributed training and inference tools, including DeepSpeed, FSDP, Megatron, ZeRO, and Ray
Engineering discipline and ability to write readable, robust, maintainable code
Experience optimising for GPU constraints, including quantisation, mixed precision, and memory
Comfortable taking ownership of ambiguous problems from zero to one
Ability to ship, iterate, and learn from production
Будет плюсом: LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer), RLHF (PPO, DPO, ORPO), open-source contributions to ML or systems libraries, scientific computing, compiler or GPU kernel experience, multimodal or diffusion model background, large-scale data processing (Arrow, Spark, Ray)
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