- Refining use-cases,
- Selecting resources needed (ML Ops, governance, compute instances, pipelines, storage, etc),
- Analyse and pre-process data if necessary,
- Building pipelines,
- Choosing foundation models,
- Fine-tuning and/or pre-training models,
- Deploying and testing proofs of concept
- Demonstrable hands-on knowledge of applied generative AI models, mainly in in text, knowledge classification and recommendation engines
- 1+ years Experience fine-tuning and/or pre-training Large Language Models for customised applications, applying this knowledge to practical scenarios,
- 5+ years Experience working with GCP (Google Cloud Platform) building Machine Learning applications and deploying cloud resources in a production environment.
- Knowledge of ML ops frameworks
- Proficient with Python or R as well as relevant frameworks (Keras, PyTorch)
- Experience in Gen Ai
- Flexible, curious, and ambitious
- Good communicator
- Eagerness to learn new techniques, solve problems and contribute in a team environment
- Hybrid- Texas, Austin
- Salary: Up to $210,000 + Benefits + Bonus
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Machine Learning Engineer - Oklahoma City, United States - NLP PEOPLE
Description
Machine Learning Practitioner – Applied LLM/ Gen Ai/ GCP – Up to $210,000- HybridRole Description
Working with a Private Equity portfolio company, you will be part of a special task team focused on building, testing and scaling applications of Generative AI and analytics to improve revenue, product features and efficiencies across the company.
Requirements:
Skills:
Job Description:
For more information or to apply for the Machine learning position, please email
or you can apply through You can also visit our vacancy page to see other opportunities
Company:
Digital Republic Talent
Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):
Senior (5+ years of experience)
How to apply:
Please mention NLP People as a source when applying
Tagged as:
Classification ,
Industry ,
Language Modeling ,
Machine Learning ,
NLP ,
Unspecified
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