Machine Learning Architect - Not An Active Opening, Building Talent Pipeline

Caylent

USA, United States
Base: $140,000 - $157,500 py; bonus/equity: compet...
On-site
Amazon sagemaker expertise
Iac tools cloudformation terraform
Ml libraries tensorflow pytorch scikit-learn
Caylent is building a talent pipeline for future opportunities, seeking a Machine Learning Architect with expertise in ML system design and AWS solutions. The role emphasizes collaboration, technical proficiency, and customer engagement, while offering a range of benefits

Job Summary

  • The role involves guiding teams through Agile ceremonies and translating customer requirements into actionable engineering backlogs.
  • Candidates must possess expert-level experience with Amazon SageMaker and various ML libraries to design robust ML systems.
  • The position offers competitive benefits including unlimited paid time off, a 401k match up to 4%, and phantom equity.

Matching Summary

Match Score: 85

Caylent is building a talent pipeline for future opportunities, seeking a Machine Learning Architect with expertise in ML system design and AWS solutions. The role emphasizes collaboration, technical proficiency, and customer engagement, while offering a range of benefits.

Salary

Base: $140,000 - $157,500 per year; Bonus/Equity: Competitive phantom equity and potential bonuses; Benefits: Medical, dental, vision, 401k match, PTO

Skills & Requirements

Must-have

  • Amazon SageMaker expertise
  • IaC tools CloudFormation Terraform
  • ML libraries TensorFlow PyTorch Scikit-learn
  • MLOps tools MLflow Neptune Comet
  • AWS cloud native application development
  • DevOps pipeline automation CI/CD

Nice-to-have

  • Passion for staying curious
  • Mentoring less experienced teammates
  • Agile ceremony facilitation skills
  • Customer requirement translation ability
  • Cross-stakeholder collaboration experience

Key Requirements

  • Expert level experience in Amazon SageMaker
  • Strong understanding of feature engineering and hyperparameter tuning
  • Familiarity with MLOps tools like MLflow and Neptune
  • Experience with Infrastructure as Code tools
  • Ability to troubleshoot production environments

Work Rights

Not specified

Tailored Resume

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