153 Quantization Jobs - Page 7

Job Description: We are looking for a passionate and highly motivated Research Engineer to join our team and contribute to the advancement of Language Model capabilities. As part of our team, you will play an integral role in researching and implementing cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and other state-of-the-art methods to enhance the performance of our models. If you are excited about working on innovative technologies, fine-tuning models, and building scalable AI systems, this is the perfect opportunity for you! Key Responsibilities: Engage in research and implementation of Retrieval-Augmented Generation (RAG) and other advanced techniques to enhance Language model capabilities. Participate in data preparation for fine-tuning processes. Assist in setting up and optimizing the pipeline for fine-tuning, Quantization. Participate in the training of small transformer models, ensuring performance and efficiency. Contribute to the development of an internal orchestration framework for LLM. Collaborate with senior engineers to integrate LLM SW Components into the existing system architecture. Support the deployment and monitoring of models in production environments. Document processes, workflows, and findings to ensure knowledge sharing and reproducibility. Qualifications: Strong Python skills. Experience with Data Wrangling and Preprocessing. Familiarity with LangChain, LlamaIndex, and VectorDB. Good understanding of transformer architecture, embeddings, and tokenizers. Experience with machine learning frameworks like TensorFlow or PyTorch. Understanding of LLMs, fine-tuning techniques, and RAG methodologies. Proficiency in version control systems (e.g., Git) and software development best practices. This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth. Company: Airbus India Private Limited Employment Type: Internship - Experience Level: Student Job Family: Digital By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus. Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief. Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com . At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

Invent, implement and deploy state-of-the-art machine learning and/or specific domain industry algorithms and systems. Build prototypes and explore conceptually new solutions. Work collaboratively with science, engineering, and product teams to identify customer needs in order to create and implement solutions, promote innovation and drive model implementations. Applies data science capabilities and research findings to create and implement solutions to scale. Responsible for developing new intelligence around core products and services through applied research on behalf of our customers. Develops models, prototypes, and experiments that pave the way for innovative products and services. Build cloud services that work out of the box for enterprises, e.g. decision support, anomaly detection, forecasting and recommendations), natural language processing (NLP), Natural Language Understanding (NLU),Time Series, Automatic Speech Recognition (ASR), Machine Learning (ML), and Computer Vision (CV). Design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. Conversant on ethical problems in consideration of sciences. Identify data science use cases and design scalable solutions that can be built as a feature of the product/service. Contributes to writing production model code. Work with Software Engineering teams to deploy them in production. Set up environment needed to run experiments for all projects. Set up distributed environments. Design and implement algorithms, train models, and deploy both to production to validate premises and achieve goals. Design and execute offline/online experiments and model performance testing. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Address business/customer problems and questions using statistical and machine learning techniques to achieve business goals and KPI's. Come up with innovative solutions to address tradeoffs or challenges faced by team. Stay up-to date with research and trends regarding latest algorithms in ML or other industry/domain space. Perform research in emerging areas, which may include efficient neural network development including quantization, pruning, compression and neural architecture search, as well as novel differentiable compute primitives. May perform other duties as assigned.

Invent, implement and deploy state-of-the-art machine learning and/or specific domain industry algorithms and systems. Build prototypes and explore conceptually new solutions. Work collaboratively with science, engineering, and product teams to identify customer needs in order to create and implement solutions, promote innovation and drive model implementations. Applies data science capabilities and research findings to create and implement solutions to scale. Responsible for developing new intelligence around core products and services through applied research on behalf of our customers. Develops models, prototypes, and experiments that pave the way for innovative products and services. Build cloud services that work out of the box for enterprises, e.g. decision support, anomaly detection, forecasting and recommendations), natural language processing (NLP), Natural Language Understanding (NLU),Time Series, Automatic Speech Recognition (ASR), Machine Learning (ML), and Computer Vision (CV). Design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. Conversant on ethical problems in consideration of sciences. Identify data science use cases and design scalable solutions that can be built as a feature of the product/service. Contributes to writing production model code. Work with Software Engineering teams to deploy them in production. Set up environment needed to run experiments for all projects. Set up distributed environments. Design and implement algorithms, train models, and deploy both to production to validate premises and achieve goals. Design and execute offline/online experiments and model performance testing. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Address business/customer problems and questions using statistical and machine learning techniques to achieve business goals and KPI's. Come up with innovative solutions to address tradeoffs or challenges faced by team. Stay up-to date with research and trends regarding latest algorithms in ML or other industry/domain space. Perform research in emerging areas, which may include efficient neural network development including quantization, pruning, compression and neural architecture search, as well as novel differentiable compute primitives. May perform other duties as assigned.