Aartificial intelligence, Data pipelines, Data science techniques, Data Visualization, Deep Learning, Design, FastAPI, Flask, Generative AI, Jupyter Notebook, Keras software library, LangChain, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), OpenAPI, Python Programming, Scikit-learn, TensorFlow
As a Data Scientist at IBM, you will help transform our clients’ data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it’s investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.
Your Role and Responsibilities
Design and implement scalable and efficient data architectures to support generative AI workflows. fine tune and optimize large language models (LLM) for generative AI, conduct performance evaluation and benchmarking for LLMs and machine learning models, apply prompt engineer techniques as required by the use case , design and implement data pre/post processing, , collaborate with research and development teams to build large language models for generative AI use cases, plan and breakdown of larger data science tasks to lower level tasks, lead junior data engineers on tasks such as design data pipelines, dataset creation, and deployment, use data visualization tools, machine learning techniques, natural language processing , feature engineering, deep learning , statistical modelling as required by the use case.
Required Technical and Professional Expertise
Skills:
Preferred Technical and Professional Expertise
Skills:
IBM is a leading cloud platform and cognitive solutions company. Restlessly reinventing since 1911, we are the largest technology and consulting employer in the world, with more than 290,000 employees serving clients in 177 countries. IBM Research provides unparalleled insight into business, industry and society by leveraging advanced computing architectures and methodologies to solve some of the world’s most pressing challenges.
Research Triangle Park, Durham, NC, USA
2-4 year
Research Triangle Park, Durham, NC, USA
2-4 year
Cambridge, MA, USA
2-4 year
San Jose, CA, USA
2-4 year
Mountain View, CA, USA
2-4 year
Rio de Janeiro, Brazil
0-2 year
Hortolândia, State of São Paulo, Brazil
0-2 year
Rio de Janeiro, Brazil
0-2 year
Hortolândia, State of São Paulo, Brazil
0-2 year
Yorktown Heights, NY, USA
0-2 year
Yorktown Heights, NY, USA
0-2 year
Cambridge, MA, USA
0-2 year
Toronto, ON, Canada
0-2 year
Calgary, AB, Canada
0-2 year
Montreal, QC, Canada
0-2 year
Givatayim, Israel
0-2 year
Cluj-Napoca, Romania
2-4 year
Research Triangle Park, Durham, NC, USA
4-6 year
Givatayim, Israel
0-2 year
Givatayim, Israel
0-2 year
Givatayim, Israel
0-2 year
Givatayim, Israel
0-2 year
São Paulo, State of São Paulo, Brazil
2-4 year
Rio de Janeiro, State of Rio de Janeiro, Brazil
2-4 year
São Paulo, State of São Paulo, Brazil
2-4 year
Rio de Janeiro, State of Rio de Janeiro, Brazil
2-4 year
Rio de Janeiro, State of Rio de Janeiro, Brazil
0-2 year
Frankfurt, Germany
4-6 year
Ehningen, Germany
4-6 year
Austin, TX, USA; Chicago, IL, USA; Dallas, TX, USA; Houston, TX, USA; Los Angeles, CA, USA; New York, NY, USA; Philadelphia, PA, USA; Phoenix, AZ, USA; San Antonio, TX, USA; San Diego, CA, USA; San Jose, CA, USA
2-4 year
Austin, TX, USA; Chicago, IL, USA; Dallas, TX, USA; Houston, TX, USA; Los Angeles, CA, USA; New York, NY, USA; Philadelphia, PA, USA; Phoenix, AZ, USA; San Antonio, TX, USA; San Diego, CA, USA; San Jose, CA, USA
2-4 year
Austin, TX, USA; Chicago, IL, USA; Dallas, TX, USA; Houston, TX, USA; Los Angeles, CA, USA; New York, NY, USA; Philadelphia, PA, USA; Phoenix, AZ, USA; San Antonio, TX, USA; San Diego, CA, USA; San Jose, CA, USA
2-4 year
Chicago, IL, USA; Columbus, OH, USA; Detroit, MI, USA; Indianapolis, IN, USA; Kansas City, MO, USA; Milwaukee, WI, USA; Minneapolis, MN, USA; Omaha, NE, USA
2-4 year