Staff Machine Learning Engineer

Automation Anywhere

San Jose, CA, US
Base: $155,000 – $175,000; bonus/equity: discretio...
Hybrid
Machine learning systems at scale
Generative ai, nlp, computer vision
Mlops best practices
This role will design, build, and deploy cutting-edge machine learning systems advancing Generative AI, Natural Language Processing, and Computer Vision capabilities within our industry-leading platform

Job Summary

  • This role will design, build, and deploy cutting-edge machine learning systems advancing Generative AI, Natural Language Processing, and Computer Vision capabilities within our industry-leading platform.
  • You will architect robust ML infrastructure, champion modern MLOps practices, and optimize performance, scalability, and reliability across distributed environments.
  • The base salary range for this position is $ 155,000 – $175,000 a year, and this position is also eligible for a discretionary bonus, equity and a full range of medical and other benefits.

Matching Summary

This role will design, build, and deploy cutting-edge machine learning systems advancing Generative AI, Natural Language Processing, and Computer Vision capabilities within our industry-leading platform.

Salary

Base: $155,000 – $175,000; Bonus/Equity: discretionary bonus, equity; Benefits: full range of medical and other benefits

Skills & Requirements

Must-have

  • Machine Learning systems at scale
  • Generative AI, NLP, Computer Vision
  • MLOps best practices
  • Python, TensorFlow, PyTorch
  • Scalable ML pipelines
  • Cloud-based ML platforms

Nice-to-have

  • Translate research into production
  • Technical leadership opportunity
  • Connect technical solutions to business objectives
  • Curiosity and agility in AI/ML advancements

Key Requirements

  • 7+ years hands-on ML experience
  • Expertise in NLP, Computer Vision, Generative AI
  • Experience taking ML models to production
  • Proficiency in Python, R, SQL
  • Experience with big data technologies
  • Experience with ML frameworks (TensorFlow, PyTorch)
  • Experience building end-to-end ML pipelines
  • Experience implementing MLOps best practices
  • Experience with cloud ML platforms
  • Experience with containerization and orchestration tools
  • Experience fine-tuning LLMs preferred
  • Familiarity with distributed training preferred

Work Rights

Authorized to work in the United States

Tailored Resume

Cover Letter