Job description

About Eightfold.ai: Eightfold is a global leader in AI-native enterprise talent intelligence, trusted by the world's largest and most respected Fortune 500 organizations. Our platform is built from the ground up, operating at scale across Azure and AWS, deployed in multiple regions globally, including IL4-compliant environments for the US Government, supporting users in 100+ countries and 30+ languages. Today, Eightfold is at the forefront of agentic AI, delivering intelligent agents that actively drive outcomes across hiring and talent workflows, while much of the industry is still experimenting with prototypes. We are defining the next era of agentic talent systems. What sets Eightfold apart is not just the technology and our mission, but the team behind it. We are a deeply technical, execution-driven organization that values ownership, collaboration, and high standards. Our engineers, product leaders, and go-to-market teams work closely together—in person and across functions—to build systems that scale in the real world. If you're excited to work on hard problems, move with urgency, and raise the bar every day, Eightfold is the place to build agentic systems that transform how the world works. About the ML Team: Our AI/ML team is building the core technology that makes our platform autonomous and agentic. We focus on real-world reliability, shipping systems that manage multi-step reasoning and distributed state management at enterprise scale. You will work with a large database of career trajectories to build intelligent agents that proactively assist millions of users across 100+ countries and 30+ different languages. Responsibilities: • Lead the team in: research, design, development, and deployment of advanced AI agents and agentic systems. • Architect and implement complex multi-agent systems, including planning, decision-making, and execution capabilities. • Own, train, build, and deploy cutting-edge deep learning models across all Eightfold products, end to end. • Develop and integrate large language models (LLMs) and other state-of-the-art AI techniques to enhance agent autonomy and intelligence. • Build robust, scalable, and reliable infrastructure to support the deployment and operation of AI agents at scale. • Diagnose and troubleshoot issues in complex distributed environments and optimize system performance. • Contribute to the team's technical growth and knowledge sharing. • Stay up-to-date with the latest advancements in AI research and agentic AI and apply them to our products. • Leverage enterprise data, market data, and user interactions to build intelligent and personalized agent experiences. Qualifications: • Knowledge and passion in machine learning algorithms, Gen AI, LLMs, and natural language processing (NLP). • Understanding of agent-based modeling, reinforcement learning, and autonomous systems. • Ability to innovate, as proven by a track record of software artifacts or academic publications in applied machine learning. • Experience with large language models (LLMs) and their applications in Agentic AI. • Proficiency in programming languages such as Python, and experience with machine learning frameworks like TensorFlow or PyTorch. • Experience with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes). • Understanding of distributed system design patterns and microservices architecture. • Excellent problem-solving and data analysis skills. • Strong communication and collaboration skills. • Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related field, or equivalent years of experience. • Min 5-7+ years of relevant work experience in AI, Machine Learning, and applying data science to real-world use cases. OR • Strong track record of taking systems from prototype to production with a focus on scalability and reliability. • Knowledge of fine-tuning strategies (QLORA, DPO) and inference optimization (vLLM, TensorRT-LLM). Desired Skills & Experience: • Research experience in agentic AI or related fields. • Experience building and deploying AI agents in real-world applications. Pay Transparency Please note this role is categorized as hybrid in Zone A: Santa Clara, CA The base salary ranges below are provided for pay transparency. Base pay is only one piece of our total compensation package as this role is also eligible for annual bonus and equity awards. Compensation varies depending on a number of factors including qualifications, skills, competencies, experience and zones (determined by location). Zone A: Base annual salary range: $193,125 to $257,500 + annual performance bonus up to 15% + preIPO equity (stock options). 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 May 1, 2025, employees residing near Santa Clara, CA office location will return to the office three days 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, veteran or disability status. 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. #LI-Hybrid

Requirements

Must-haves

Lead the team in: research, design, development, and deployment of advanced AI agents and agentic systems.
Architect and implement complex multi-agent systems, including planning, decision-making, and execution capabilities.
Own, train, build, and deploy cutting-edge deep learning models across all Eightfold products, end to end.
Develop and integrate large language models (LLMs) and other state-of-the-art AI techniques to enhance agent autonomy and intelligence.
Build robust, scalable, and reliable infrastructure to support the deployment and operation of AI agents at scale.
Diagnose and troubleshoot issues in complex distributed environments and optimize system performance.
Contribute to the team's technical growth and knowledge sharing.
Stay up-to-date with the latest advancements in AI research and agentic AI and apply them to our products.
Leverage enterprise data, market data, and user interactions to build intelligent and personalized agent experiences.
Knowledge and passion in machine learning algorithms, Gen AI, LLMs, and natural language processing (NLP).
Understanding of agent-based modeling, reinforcement learning, and autonomous systems.
Ability to innovate, as proven by a track record of software artifacts or academic publications in applied machine learning.
Experience with large language models (LLMs) and their applications in Agentic AI.
Proficiency in programming languages such as Python, and experience with machine learning frameworks like TensorFlow or PyTorch.
Experience with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes).
Understanding of distributed system design patterns and microservices architecture.
Excellent problem-solving and data analysis skills.
Strong communication and collaboration skills.
Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related field, or equivalent years of experience.
Min 5-7+ years of relevant work experience in AI, Machine Learning, and applying data science to real-world use cases. OR
Strong track record of taking systems from prototype to production with a focus on scalability and reliability.
Knowledge of fine-tuning strategies (QLORA, DPO) and inference optimization (vLLM, TensorRT-LLM).
Research experience in agentic AI or related fields.
Experience building and deploying AI agents in real-world applications.

Nice-to-haves

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Keywords to mirror

aiazureawsgomlmachine learningpythondockerkubernetesllm

Platform: eightfold
Effort: medium

Benefits

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Dental

Vision