HI there
two weeks of bootcamp to cover these topics with practical... how much would you charge?
• Generative AI
o Machine Learning
o Deep Learning
o Reinforcement Learning
o Natural Language Processing
o Optimization
o Probabilistic Inference
o Information Retrieval
o Recommendation Systems
o Bayesian Inference
o Advanced time series forecasting
• Hands-on Experience with most of the following open-source solutions:
o Orchestrate: Airflow, Kubeflow Pipelines, ML Run
o Container: Docker, Kubernetes, Mesos + Marathon
o Model Serving: Kubeflow KF Serving, TF Serving, Seldon-Core, MLflow
o Observability: Prometheus, Grafana, Elasticsearch
o Development:
• Programming Language: Python, Java, Scala, Julia
• IDE: Notebooks, PyCharm, VS Studio
• Machine Learning: TensorFlow, Keras, ScikitLearn, H20.ai, XGBoost, MXNet
• Feature Store: Hopsworks, Feast, or other purposed built Feature Store
• Experience with at least one ML project, either academic or personal, showcasing understanding of the end-to-end ML lifecycle
• Experience with Large Language Models (LLMs) and Transformers is a plus (e.g., Hugging Face, AutoTrain, PyTorch, PyG, OpenAI, or other relevant APIs)
• Familiarity with cloud platforms (AWS preferred) for deploying ML models is a plus
• Experience in machine learning frameworks (Scikit-learn, Tensorflow, Pytorch), big data frameworks (Spark/Hadoop/Flink) and experience in resource management and task scheduling
• Proficient in Python & SQL.
• Generative AI frameworks and libraries: Hugging Face Transformers, OpenAI, and GPT-based APIs
• Experience in ML pipeline, model training orchestration
• experience with AI, Retrieval Augmented Generation and LLMs