AI/ML Research EngineerPosition is with Google ML Engineering team - must be willing to work 100% onsite - 5 days a week in San Jose CA. Looking for strong experience with Python, C++, and building ML models from scratch.Basic questions asked in the phone interview:How strong he/she is Tensorflow and Keras?What are ML frameworks used apart from Tensorflow and Keras?Supervisor Learning and unsupervised learningDifference between classification and regressionOverfitting vs. underfittingDifference between Precision and recallDifference between Shallow copy and deep copy?Experience with Gemini/GemmaThe candidate must be strong on Python coding, must be good with the tools and will be working closely with the ML team in improving the existing models and will be writing models in Python, C++, PySpark & LLM, API Keras, Keras hub, Keras3.
Scope for GenAI, notebooks and work on the core side.Interview process:1st round - Phone screening - 20 minutes phone call asking basic questions on Python, ML frameworks.2nd round - Coding interview + HR round - Questions will be mainly related to Python coding and Data scienceAI/ML Research Engineer - Job DescriptionSeeking a SWE with Al/ML/Gen Al/ Prompt engineering experience with hands-on coding in C++/python. Working on production level coding in Python/C++ is preferredMachine Learning PrerequisitesOverview of ML explaining life cycle like Data Acquisition-> Cleaning-> Training a model > Testing a model-> Evaluating a modelKnowledge on deploying models on mobile devices iOS/AndroidKnowledge on C++ for custom functions and writing unit test cases.Strong debugging skills on C++/Python code.Basic jargons of ML which include Cost functions, Gradient Descent, Back Propagation, Activation functions etcSupervised, Unsupervised, Reinforcement learningClassifications and RegressionUsing DatasetsTypes of algorithms like Decision Tree, K means etcUsing scientific Python libraries numpy, pandas, matplotlib, scikit-learnImporting data in python, clean, preprocess data and manipulate data frames with pandasNeural networks, CNN, RNN/LSTM, LLM, Generative Al, Prompt engineeringMinimum QualificationsMasters degree/PhD in Computer Science & Data Science/Al ML or a related technical field or equivalent practical experience.2+ years of work experience in Machine Learning or Artificial Intelligence using tensorflow and Keras or equivalent. Working knowledge with Generative Al, LLM products like Gemini, Ollamma, Mistral or Open Al etc is a must.
Knowledge in Prompt engineering, Gemma and/or Gemini is a plusStrong debugging skills on C++/Python code.Basic jargons of ML which include Cost functions, Gradient Descent, Back Propagation Activation functions etcSupervised, Unsupervised, Reinforcement learningClassifications and RegressionUsing DatasetsTypes of algorithms like Decision Tree, K means etcUsing scientific Python libraries numpy, pandas, matplotlib, scikit-learnImporting data in python, clean, preprocess data and manipulate data frames with pandasNeural networks, CNN, RNN/LSTM, LLM, Generative Al, Prompt engineeringMinimum QualificationsMasters degree/PhD in Computer Science & Data Science/Al ML or a related technical field or equivalent practical experience.2+ years of work experience in Machine Learning or Artificial Intelligence using tensorflow and Keras or equivalent. Working knowledge with Generative Al, LLM products like Gemini, Ollamma, Mistral or Open Al etc is a must.Knowledge in Prompt engineering, Gemma and/or Gemini is a plusExperience with one or more general purpose programming languages including but not limited to: Python, Java, or C/C++ etc.Experience working with Windows, MacOS, and Ubuntu environmentsExcellent written and oral communication skillsBeing a team player with a positive attitude and people skillsOpen to learning new internal technical tools