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About the AI/ ML TeamThe AI / Machine Learning team is building the industry's leading Machine Learning models for use cases at scale. This team is also responsible for pushing the boundaries of applied Machine Learning and state-of-the-art Generative AI techniques on a challenging and diverse dataset. The team is at the forefront of building frameworks for Responsible AI development.
What you will do (learn to do)
You will own, build, train and productionize cutting-edge ML models across all Eightfold products, end to end - in production.
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
Do it responsibly to provide 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 train, update and evaluate Large Language Models (LLMs) What you bring
Good foundation in Machine Learning (ML), Deep Learning, Large Language Models (LLM) and Natural Language Processing (NLP).
Hands-on experience in applying Natural Language Processing (NLP) solutions is a plus.
Ability to work cross functionally & interface with Data Scientists
Familiar with Large Language Models, transformers like BERT, GPTs, T-5, HuggingFace etc.
Strong knowledge of CS fundamental concepts and ML languages ( like Python, C, C++, Java, JavaScript, R, and Scala, etc. )
Ability to innovate, as proven by a track record of software artifacts or academic publications in applied machine learning.
Understanding of data and/or ML systems with ability to think across layers of the stack - REST APIs, microservices, data ingestion and processing systems, and distributed systems.Nice To Haves
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
Solid understanding of machine learning theory
Metrics-focused and passionate about delivering high quality models.
Familiar with Pandas or Python machine learning libraries
Familiar with Spark, MLLib, Databricks MLFlow, Apache Airflow and similar related technologies.
Familiar with a cloud based environment such as AWS
Experience with analyzing large data sets, using Hadoop, Spark or related technologies is a plus.
Pay Transparency*Please note this role is open in Santa Clara, CA location and categorized as onsite in HQ Office. The base salary ranges below are provided for pay transparency. Base pay is only one piece of our total compensation package as this role may be eligible for annual bonus and equity awards. Compensation varies depending on a number of factors including qualifications, skills, competencies, and experience and zones. Zones are determined by location.
Zone A: USD $144,000 - $169,000 base annual salary +bonus
Hybrid Work @ Eightfold: We embrace a hybrid work model that aims to boost collaboration, enhance our culture, and drive innovation through a blend of remote and in-person work. We are committed to creating a dynamic and flexible work environment that nurtures the collaborative spirit of our team. Starting February 1, 2024, employees residing near Santa Clara, California, or our Bangalore and Noida offices in India will return to the office twice a week.Eightfold.ai provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, or disability.Experience our comprehensive benefits with family medical, vision and dental coverage, a competitive base salary, and eligibility for equity awards and discretionary bonuses or commissions. ]]>