Description
We are seeking an experienced MLOps Engineer with deep expertise in cloud services such as Azure ML and AWS SageMaker, providing end-to-end MLOps operations and services.
Responsibilities
•Develop and optimize MLOps pipelines for scalable model development and deployment
•Automate model training, deployment, monitoring, and testing workflows
•Manage data pipelines, ensuring efficient training data preparation
•Implement model performance tracking and versioning using MLflow
•Deploy and fine-tune open-source LLM models for various business use cases
•Utilize vLLM, LiteLLM, BentoML, Ollama for optimized LLM inference and deployment
•Monitor and evaluate LLM performance across different metrics including latency, accuracy, and cost-effectiveness
•Develop AI-based solutions for product category classification and product data enrichment
•Implement dynamic price optimization models and forecast price and demand trends
•Build AI systems to select optimal recommerce channels for selling products, based on various business factors, including price seasonality and inventory costs
Requirements
•End-to-end ML pipelines (Azure ML, AWS SageMaker, MLflow), Docker, Kubernetes, CI/CD for ML
•Deploying open-source LLMs (Llama, Mistral, R1), optimizing LLM inference, RAG, fine-tuning
•Python, ML frameworks (PyTorch, TensorFlow), microservices, data pipelines
•Evaluating and fine-tuning ML/LLM models, tracking metrics, optimizing AI solutions
•Middle level position, 24 months of experience
Conditions
•Flexible working conditions and a cooperative environment
•Competitive salary
•Many challenging and exciting projects with new opportunities and learning
•Growth opportunities, skills and competencies improvement, and professional certification
•In-company training (English, Software / DevOps / Project management / Design / Business)
•A friendly team of 150+ professionals, with support from colleagues and investment in additional education and certification
