Predii
Website:
predii.com
Job details:
This is a full time role for a LLM Research Engineer As a part of your daily duties, you will
- Work on the Predii platform building and enhancing LLM models for question and answering
- Fine-tune using synthetic and proprietary data sets,
- Productize back end services using microservices, REST APIs, ML and NLP libraries, customized algorithms, and NoSQL datastores.
- Conduct core research and also apply to automotive ecosystem.
- Take ownership as an Individual contributor of design and develop algorithms, maintain, develop, and improve Predii LLM models and software used in these models
- Support in building libraries and framework that support large complex web applications.
- Contribute to engineering efforts by using your programming skills from planning to execution in development of efficient, scalable, distributed solution to real world problems.
- Work with cross-functional teams, customers and open-source communities.
- Opportunity to take part in building new industry-changing services in our portfolio and participate in state-of-the-art research in LLMs.
Qualifications
- Bachelor’s/Master’s in Computer Science or related fields or PhD in NLP/ML/LLM (one who have submitted their thesis is eligible to apply)
- 2-3+ years of professional experience in production environment. For PhD holders, working experience in a relevant lab setting coupled with top-tier publications (A/A*) would waive the professional experience requirement
- Excellent knowledge of Computer Science fundamentals (Algorithms, Data Structures, Operating system)
- GoodProgramming skills (at least one of Python/Java)
- Experience in data analysis libraries such as Pandas
- Experience with LLMs fine-tuning, LLM Prompt Engineering, LLM evaluation frameworks
- Experience with Transformers architecture, Embedding models, Hugging face model publishing/inferencing
- Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
- Experience in machine learning, supervised and unsupervised: Forecasting, Classification, Data/Text Mining, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms
- Experience in statistical learning: Predictive & Prescriptive Analytics, Regression, Time Series, Topic
- Previous experience working with multimodal systems
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