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aitechrwaweb3
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About this role
Join Ural Logistics as an ML Engineer to build data pipelines and optimize models using Python and PyTorch in a hybrid work environment.
Description
Join Ural Logistics as an ML Engineer to build data pipelines and optimize models using Python and PyTorch in a hybrid work environment.
Responsibilities
Responsibilities
- Build data preparation pipelines: collection, cleaning, normalization, deduplication, and annotation
- Form training, validation, and independent evaluation datasets, control leaks and overlaps
- Create baselines for extraction, classification, entity and relationship recognition tasks
- Fine-tune models, prepare instructional datasets, train adapters, and compare results with baseline models
- Define metrics, stratify samples, and analyze errors by document types, scenarios, and fields
- Work on entity and relationship extraction to build and update graph representations of data
- Deploy local inference and optimize it for available infrastructure
- Work with tensor parallelism, batching, context length, GPU memory, and quantization
Requirements
Requirements
- Stack: Python, PyTorch, Hugging Face Transformers, PEFT, pandas, SQL, PostgreSQL, Airflow (or similar), MLflow (or similar), vLLM, CUDA, Docker, Kubernetes
Job Details
Market range (est.)$90k–$180k
LocationHybrid
AI Score★★★★★★☆☆☆☆ 6/10
PostedSep 24, 2026 (18d ago)
Tags & Skills
aitechrwaweb3cryptoML Engineerhybrid
Tech Stack
PythonPyTorchHugging Face TransformersPEFTpandasSQLPostgreSQLAirflowMLflowvLLMCUDADockerKubernetes
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