Machine Learning Engineer

Eightfold • Full-time • Hybrid in Santa Clara, California, United States • 1h ago

Fast Facts

Join our team as a Machine Learning Engineer to research and develop advanced AI agents and multi-agent systems, enhancing autonomy and intelligence in real-world applications.

Responsibilities: Research, design, and deploy AI agents; collaborate with cross-functional teams; optimize performance in distributed environments; contribute to the development of intelligent agent experiences.

Skills: Proficiency in Python, machine learning frameworks (TensorFlow or PyTorch), cloud platforms (AWS), containerization (Docker, Kubernetes), and strong problem-solving skills.

Qualifications: Master's or Ph.D. in Computer Science, Artificial Intelligence, or related field; 1-3+ years of relevant experience; research background in agentic AI preferred.

Location: Santa Clara, CA, US

Compensation: Not provided by employer. Typical compensation ranges for this position are between $120,000 - $180,000.

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, Gen AI, LLMs, and natural language processing (NLP). 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 TensorFlow 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. Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field, or equivalent years of experience. Min 1-3+ 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.