Eightfold.Ai - Santa Clara, CA

posted 2 months ago

Full-time - Mid Level
Santa Clara, CA

About the position

At Eightfold AI, we are at the forefront of transforming talent management through our AI-powered Talent Intelligence Platform™. Our mission is to help organizations identify, attract, and retain top talent while empowering employees with the tools they need to thrive in their careers. As part of the AI/Machine Learning team, you will be instrumental in developing industry-leading machine learning models that address real-world challenges in the HR Tech industry, which is valued at $400 billion. This role offers the opportunity to work with large datasets and push the boundaries of applied machine learning in a fast-paced startup environment that values innovation and collaboration. In this position, you will be responsible for developing, training, and productionizing cutting-edge machine learning models across all Eightfold products. You will leverage open-source large language models and apply innovative solutions from generative AI to create industry best practices for machine learning in recruiting and HR. Your work will help ensure equal opportunity for everyone by extending our internal model fairness platform, and you will create innovative algorithms for machine learning and AI applications. Additionally, you will implement best practices for building AI-enabled products and develop AI-based systems for natural language processing (NLP). Your role will also involve optimizing machine learning models for time efficiency, performance, cost, scalability, and accuracy. You will develop tools and processes for automatically training, updating, and evaluating large language models, and you will have the opportunity to train and mentor junior machine learning engineers, fostering a culture of learning and growth within the team.

Responsibilities

  • 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
  • Train and mentor junior Machine Learning Engineers

Requirements

  • BS/MS in Computer Science or Engineering
  • Relevant work experience in Machine Learning (ML), Deep Learning, and NLP
  • Experience with implementing production machine learning systems and working with large-scale datasets
  • Strong knowledge of CS fundamental concepts and ML languages (Python, C, C++, Java, R, and Scala, etc.)
  • Experience with scientific libraries in Python (numba, pandas) and machine learning tools and frameworks (scikit-learn, tensorflow, torch, 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

Nice-to-haves

  • Familiarity with GenAI, LLMs (large language models, transformers like BERT, GPT-3, T-5), etc.
  • 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 is a plus

Benefits

  • Family medical coverage
  • Vision coverage
  • Dental coverage
  • Competitive base salary
  • Eligibility for equity awards
  • Discretionary bonuses or commissions
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