Senior Machine Learning Engineer
Core
Design, fine-tune, and deploy Large Language Models and predictive analytics systems for regulatory document intelligence and supply chain optimization.
Role type
Senior Machine Learning Engineer (Generative AI & Supply Chain)
Builds
LLM pipelines for rule extraction from regulatory texts; time-series forecasting and anomaly detection models for supply chain; MLOps infrastructure for on-premise deployment.
Domain
Enterprise software, Supply Chain Management, Regulatory Compliance
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, Transformer architectures (BERT, GPT, Llama), NLP frameworks (Hugging Face, LangChain), MLOps tools (Kubeflow, MLflow), Docker, Kubernetes, SQL, Graph traversal algorithms
Preferred skills
Few-shot learning, Chain-of-thought prompting, Model quantization and distillation, Multi-objective optimization, RAG architectures
Technologies
Docker, Kubernetes, Kubeflow, MLflow, Hugging Face, LangChain, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, SQL
Responsibilities
Design and fine-tune LLM pipelines to interpret regulatory texts and extract structured rules; Develop time-series forecasting models for material demand and spend prediction; Build classification and anomaly detection models for supplier risk assessment; Containerize and deploy models into secure on-premise inference environments; Build automated training and inference pipelines to ensure reproducibility; Optimize model inference latency and resource usage for efficient hardware utilization.
Seniority
Senior, hands-on IC