Master’s or PhD’s degree in Data Science, Computer Science, or a related field
Proven extensive industry experience in driving, designing, and developing AI/GenAI and ML solutions for challenging and complex problems (digital assistant, time series prediction, anomaly detection, etc.), particularly in the area of cloud infrastructure optimization
Proven track record of experience in transformer-based models, particularly LLMs, finetuning techniques, RAG, and prompt engineering
Experience with building data pipelines for LLMs, object stores, and vector databases
Proficiency in Python programming; R, Java, C/C++, Scala, etc. are plus
Strong experience with industry-leading AI/ML libraries and frameworks (PyTorch, Hugging Face, TensorFlow, etc.), as well as proficiency in working with streaming data
Good cloud infrastructure knowledge
Strong problem-solving skills and attention to detail, performance, and quality
Excellent communication and interpersonal skills to effectively convey holistic solutions and complex technical concepts, visualizing and presenting results to stakeholders
Fluency in written and spoken English
Nice to haves:
Experience in big data management and database systems
Experience in large-scale and distributed systems development