AI Engineer
1 week ago
Advanced proficiency in Python.
• Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt
engineering techniques
• Experience with big data processing using Spark for large-scale data analytics
• Version control and experiment tracking using Git and MLflow
• Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust,
expertise in microservices, test-driven development, and concurrency processing.
• DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation),
CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and
service mesh implementations.
• LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as vLLM and
FastAPI, model quantization techniques, and vector database management.
• MLOps & Deployment: Utilization of containerization strategies for ML workloads, experience with
model serving tools like TorchServe or TF Serving, and automated model retraining.
• Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network
security for ML systems.
• LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation
services, and optimizing LLMs for performance and security.
• General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face,
TensorFlow, PyTorch), and experience with cloud platforms like AWS or GCP.
• Experience in creating LLD for the provided architecture.
• Experience working in microservices based architecture.
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