Senior/principal Machine Learning Engineer

Embeda

Atlanta, GA, United States
Base: $228,000 usd - $342,000 usd; bonus/equity: e...
Fully remote
Applied machine learning products at scale
Machine learning and deep learning frameworks
Building services to host ml models in production
As a Senior/Principal Machine Learning Engineer, you will design and build the core ML systems behind Workday’s next generation of AI agents, owning the full lifecycle from problem framing to deployment and continuous improvement

Job Summary

  • As a Senior/Principal Machine Learning Engineer, you will design and build the core ML systems behind Workday’s next generation of AI agents, owning the full lifecycle from problem framing to deployment and continuous improvement.
  • The team operates with high trust, high expectations, and real impact, working at the intersection of AI, platform architecture, and human workflows with autonomy to shape scalable and responsible AI agents.
  • Workday offers a flexible work approach combining in-person and remote time, a comprehensive benefits package, and a culture rooted in integrity, empathy, and shared enthusiasm.

Matching Summary

As a Senior/Principal Machine Learning Engineer, you will design and build the core ML systems behind Workday’s next generation of AI agents, owning the full lifecycle from problem framing to deployment and continuous improvement.

Salary

Base: $228,000 USD - $342,000 USD; Bonus/Equity: Eligible for Workday Bonus Plan and stock grants; Benefits: Comprehensive benefits package

Skills & Requirements

Must-have

  • Applied machine learning products at scale
  • Machine learning and deep learning frameworks
  • Building services to host ML models in production
  • Experience with large language models and text generation
  • Cloud computing platforms expertise
  • Leading and mentoring ML engineering teams

Nice-to-have

  • Curious and courageous collaborator
  • Strong engineering judgment
  • Excellent interpersonal and communication skills
  • Ability to solve ambiguous, open-ended problems
  • Culture of collaboration and continuous improvement
  • Stay up to date with AI and orchestration frameworks

Key Requirements

  • 10+ years in applied machine learning engineering (Principal level)
  • 7+ years in applied machine learning engineering (Senior level)
  • 4+ years experience with PyTorch or TensorFlow
  • 6+ years building ML model hosting services at scale
  • 3+ years experience with large language models or graph neural networks
  • 6+ years cloud computing platform experience
  • Proven leadership and mentoring of ML teams
  • Bachelor’s degree required; Master’s or PhD preferred

Work Rights

Not specified

Tailored Resume

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