Machine Learning Engineer

ZoomZoom·Remote(Flexible / Remote)
AI & Machine Learning

WFA Digital Insight

As the demand for AI and machine learning specialists continues to soar, with over 50% of companies investing in these technologies, Zoom's Machine Learning Engineer role stands out. With a strong focus on time-series forecasting and modern LLM capabilities, this position requires a unique blend of technical skills. The current market context, where 75% of businesses face workforce management challenges, makes this role highly relevant. Candidates should be prepared to showcase their expertise in Python, ML frameworks, and software engineering best practices. Before applying, it's essential to understand the company's hybrid approach to work and the benefits that come with it, including a commitment to employee well-being and growth.

Job Description

About the Role

The Machine Learning Engineer position at Zoom is a critical part of the Workforce Engagement Management (WEM) team, tasked with developing cutting-edge AI-powered forecasting, scheduling, and adherence solutions. As a key member of this team, you will collaborate with cross-functional teams, including product, operations, and engineering, to deliver seamless AI integrations. Your primary focus will be on building intelligent WEM systems by integrating large language models (LLMs), time-series models, and optimization engines to revolutionize workforce operations management.

Day-to-day, you will work on designing and optimizing AI/ML algorithms for WEM use cases, leveraging time-series analysis and optimization frameworks for forecasting and scheduling. You will also engineer and tune LLM prompts and workflows to enhance scheduling and forecasting insights. The role involves developing evaluation frameworks and feedback loops to optimize ML model and agent performance, as well as building and optimizing infrastructure for distributed model training across multi-node, multi-GPU clusters.

What You Will Do

  • Design and optimize AI/ML algorithms for WEM use cases
  • Leverage time-series analysis and optimization frameworks for forecasting and scheduling
  • Engineer and tune LLM prompts and workflows to enhance scheduling and forecasting insights
  • Develop evaluation frameworks and feedback loops to optimize ML model and agent performance
  • Build and optimize infrastructure for distributed model training across multi-node, multi-GPU clusters
  • Collaborate with teams for seamless integration of AI/ML features into production systems
  • Contribute to design reviews, technical discussions, and code quality standards
  • Fine-tune, prompt-engineer, and orchestrate LLM pipelines to solve real-world forecasting and adherence challenges
  • Develop smart forecasting and scheduling engines that can adapt and learn from operational data

What We Are Looking For

  • Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field
  • 4-6 years of hands-on experience in AI/ML engineering roles
  • Programming skills in Python, with knowledge of software engineering best practices
  • Experience with ML frameworks (MXNet, TensorFlow, or PyTorch)
  • Solid understanding of time-series preprocessing, feature engineering, and forecasting algorithms
  • Experience with production optimization tools like CP-SAT or Google OR-Tools
  • Background in NLP and transformer-based models
  • Experience with LLMs, fine-tuning, Prompt engineering, Context engineering, MCP, and Agentic AI frameworks
  • Experience with Git, CI/CD, and scalable deployment practices

Nice to Have

  • Experience with cloud platforms (AWS, Azure, Google Cloud)
  • Knowledge of containerization (Docker) and orchestration (Kubernetes)
  • Familiarity with agile development methodologies
  • Experience with data visualization tools
  • Certification in machine learning or a related field

Benefits and Perks

  • Competitive salary and benefits package
  • Opportunities for professional growth and career advancement
  • Flexible and remote work arrangements
  • Access to cutting-edge technologies and tools
  • Collaborative and dynamic work environment
  • Comprehensive health and wellness programs
  • Generous PTO and holiday package
  • Employee stock purchase plan
  • Professional development and education assistance

How to Stand Out

  • Showcase your experience with time-series forecasting and modern LLM capabilities in your portfolio or resume.
  • Be prepared to discuss your approach to developing and optimizing AI/ML algorithms for workforce management challenges.
  • Highlight your understanding of software engineering best practices and experience with ML frameworks.
  • Practice explaining complex technical concepts in simple terms, as you will be working with cross-functional teams.
  • Research Zoom's company culture and be ready to discuss how your skills and experience align with their values and mission.
  • Consider learning more about Zoom's products and services to demonstrate your interest in the company and role.

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