Applied Scientist 2/3

/At Oracle Cloud Infrastructure (OCI), we build the future of the cloud for Enterprises as a diverse team of fellow creators and inventors

We act with the speed and attitude of a start-up, with the scale and customer-focus of the leading enterprise software company in the world

Values are OCI s foundation and how we deliver excellence

We strive for equity, inclusion, and respect for all

We are committed to the greater good in our products and our actions

We are constantly learning and taking opportunities to grow our careers and ourselves

We challenge each other to stretch beyond our past to build our future

You are the builder here

You will be part of a team of really smart, motivated, and diverse people and given the autonomy and support to do your best work

It is a dynamic and flexible workplace where you ll belong and be encouraged

In AI Data org we are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure

We are building cloud services using LLMs and other generative models for generating synthetic data for text, speech, vision and multi-modal use cases, creating ML benchmarking standards and framework to ensure highest model and data quality across various verticals including Healthcare, Fusion etc

Career Level - IC2/IC3

Key Responsibilities:

Design and build the world-class Generative AI Models in text, vision and multimodal setting for generating synthetic data


Research and Implement cutting edge techniques(Fine tuning, RLHF) in aligning Generative models to specific problem domains


Build the necessary tooling for data acquisition, data cleaning, data augmentation, model training and visualization


Evaluate and Implement the ML/Deep learning/GenAI models from research papers and other public internet resources


Optimize models for production usage and help productizing the generation scenarios to a production stetting


Develop production code for feature processing, model prediction, serving, and monitoring in both real-time and batch scenarios


Participate in the entire software lifecycle - development, testing, CI and production operations
Balance between product feature development and production operational concerns like writing run books, ops automation, structured logging, instrumentation for metrics and events

Qualifications Minimum Qualifications

Ph

D

degree or Master s degree or equivalent experience in computer science, artificial intelligence, machine learning, operations research, or related technical field


5+ years w/Masters or 3+ years w/PhD of applying machine learning for solving real-world problems in industry
Proficiency in Python or R
Proficiency with at least one deep learning library (Pytorch, Tensorflow or Keras) with building and deploying DNN models in production


Expertise in NLP, Transformers, Large Language Models, hugging face library

Optimizations around LLM training and serving


Experience applying statistical models and developing Machine Learning solutions (regression, classification, clustering)
Extensive experience with developing and serving large scale Deep learning models across different data domains


Experience in optimization and scaling of ML solutions for real world business use cases


Expertise in statistical concepts and experience with traditional ML libraries such as scikit-learn, statsmodels and pandas
Past delivery of large-scale ML solutions for complex business problems
Experience with production operations and good practices for putting quality code in production and troubleshoot issues when they arise
Take initiative and be responsible for delivering complex software by working effectively with the team and other stakeholders
Can easily communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations)