Immigration sponsorship is not available for this position

What you can expect:

As a Machine Learning Engineer on our GenAI Engineering team, you will play a critical role in shaping the future of Zoom AI through innovative engineering solutions. You'll take the lead in developing and enhancing AI algorithms, techniques, and solutions for our AI Companion product. Working closely with experienced researchers and engineers, you'll be part of a dynamic team dedicated to achieving groundbreaking results in agentic AI.

Responsibilities:

• Architectural Leadership
  • Design and evolve the architecture of ZVA and AIEA runtime services to ensure scalability, reliability, and performance.
  • Define and implement the agent runtime framework that supports multi-turn conversation understanding, contextual reasoning, and intelligent response generation.
  • Collaborate with cross-functional teams to integrate LLM-based reasoning and action orchestration into production systems.
• Team Management
  • Lead and mentor a distributed team of AI researchers, software engineers, and system architects across multiple regions.
  • Foster a culture of innovation, collaboration, and technical excellence.
  • Oversee project planning, resource allocation, and performance management to ensure timely delivery of high-quality solutions.
• Technical Strategy and Innovation
  • Drive the technical roadmap for ZVA AI and AIEA runtime services in alignment with organizational goals.
  • Evaluate emerging AI technologies and frameworks to enhance the team’s capabilities in conversational AI and agent intelligence.
  • Ensure best practices in model deployment, runtime optimization, and system observability.
• Cross-Functional Collaboration
  • Partner with product, research, and infrastructure teams to align AI capabilities with business objectives.
  • Communicate technical vision and progress to stakeholders and leadership teams.
  • Promote knowledge sharing and technical alignment across global engineering teams.

What we're looking for:

Required a bachelor's degree Computer Science, Machine Learning, Distributed Systems, a related field, or a foreign degree equivalent. Requires 5 years of experience in job offered or related occupation. Must have 5 years of experience in the following:

• 5 years of experience utilizing programming languages Python, C, C++, or CUDA;
• 5 years of experience building scalable software systems;
• 5 years of experience utilizing deep learning frameworks such as PyTorch and TensorFlow;
• 5 years of experience developing and deploying business application logic for handling requests and routing to deployed machine learning models such as LLMs, as well as, feature stores in DynamoDB, MongoDB, MySQL, and ElasticSearch;
• 5 years of experience leveraging authentication mechanisms such as Asymmetric JWT using a complex and securely designed key management system, such as AWS KMS and internally developed CSMS;
• 5 years of experience leveraging machine learning models, such as LLM prompts and agentic workflows, internally developed and third-party, and deploy them in a microservice environment powered by Docker and Kubernetes (AWS EKS), and an internal platform called ZCP, using languages such as Python and Java;
• 5 years of experience writing machine learning workflows operating on up to terabytes of data, deploy, and verify them on DataBricks using technologies like Spark and SQL.
• Telecommuting work arrangement permitted: position may work in various unanticipated locations throughout the U.S. Position does not require domestic or international travel.

Salary Range or On Target Earnings:

Minimum:

$214,080.00

Maximum:

$332,200.00

In addition to the base salary and/or OTE listed Zoom has a Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value.

Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience.

We also have a location based compensation structure;  there may be a different range for candidates in this and other locations.

Ways of Working
Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting.

Benefits
As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways. Click for more information.