Senior Machine Learning Engineer – GenAI, LLM, Agentic AI

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.

Backed by over $410M in funding and valued at $2B+, 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.

The AI Agents team  is at the forefront of developing intelligent, autonomous systems that will redefine talent management. We are building cutting‑edge agentic AI that can proactively assist users, automate complex workflows, and provide personalized insights. Our work directly impacts millions of users and shapes the future of how people connect with opportunities.

• 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.
• 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.
• Collaborate with product managers, UX designers, and other engineers to define requirements and deliver impactful solutions.
• 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.
• Contribute to the development of Copilot GenAI Workflows for Users, enabling chat‑like command execution.

• Knowledge and passion in machine learning algorithms, GenAI, LLMs, and Agentic AI
• Understanding of agent‑based modeling, reinforcement learning, and autonomous systems.
• 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 Tensor Flow or PyTorch.
• Experience with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes).
• Understanding of distributed system design patterns and microservices architecture.
• Demonstrable Coding and Algorithms skills.
• Excellent problem‑solving and data analysis skills.
• Strong communication and collaboration skills.
• Bachelors or Masters or Ph.D. in Computer Science, Artificial Intelligence, or a related field, or equivalent years of experience.
• Min 2-5+ years of relevant machine learning work experience.

• Research experience in agentic AI or related fields.
• Experience building and deploying AI agents in real‑world applications.

Please note this role is categorized as hybrid in 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 may be eligible for bonus and equity awards. Compensation varies depending on a number of factors including qualifications, skills, competencies, experience and…