- Develop, train, and productionize cutting-edge ML models across all Eightfold products
- Build on top of Open Source Large Language Models to leverage a diverse dataset
- Apply innovative solutions from Generative AI
- Create industry best practices for Machine Learning in Recruiting and HR
- Help ensure equal opportunity for everyone by extending our internal model fairness platform
- Create innovative algorithms for Machine Learning & AI
- Implement best practices for building AI-enabled products
- Develop AI-based systems for Natural Language Processing (NLP)
- Optimize Machine Learning models for time efficiency, performance, cost, scalability, and accuracy
- Develop tools and processes for automatically training, updating, and evaluating Large Language Models
- BS/MS in Computer Science or Engineering
- Good foundation in Machine Learning (ML), Deep Learning, and NLP
- Familiarity with GenAI, LLMs (large language models, transformers like BERT, GPT-3, T-5), etc.
- Strong knowledge of CS fundamental concepts and ML languages ( Python, C, C++, Java, R, and Scala, etc.)
- Understanding of data and/or ML systems with the ability to think across layers of the stack - REST APIs, microservices, data ingestion and processing systems, and distributed systems
- Passionate about delivering high-quality models
- Relevant work experience with ML/AI algorithms, tools, Deep Learning, or NLP
- Experience with scientific libraries in Python (numba, pandas) and machine learning tools and frameworks (scikit-learn, tensorflow, torch, etc.)
- Experience with implementing production machine learning systems and working with large-scale datasets is a plus
- Hands-on experience in applying Natural Language Processing (NLP) solutions is a plus
- Familiar with Spark, MLLib, Databricks MLFlow, Apache Airflow, and similar related technologies
- Experience with analyzing large data sets using Hadoop, Spark, or related technologies is a plus
- Ability to innovate, proven by a track record of software artifacts or academic publications in applied machine learning
1 applies
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