Machine Learning Engineer

RunSybil

$120K — $160K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Experience in addressing security data problems
  • 4+ years of experience in designing experiments and managing data infrastructure
  • Understanding of both modern and classic machine learning techniques
  • Proficiency with Jupyter notebooks and building data pipelines
  • Ability to thrive in ambiguous environments, seeking autonomy and creative solutions

Responsibilities

  • Propose and implement technical initiatives aligned with product needs
  • Lead technical design discussions and contribute to team decision-making
  • Translate complex technical challenges into actionable plans
  • Set and uphold high standards for code quality and engineering practices

Benefits

  • Hybrid work model in New York City
  • Opportunities for autonomy and creative problem-solving
  • Engagement in fast-paced, innovative projects
  • Potential for professional development through challenging technical initiatives
Full Job Description
About this Role

We are seeking talented engineers intent on changing the security industry. If you have experience on fast-moving teams and pushing out high quality experiments: we want to talk to you.

What You'll Do:
  • Propose and implement technical initiatives based on product roadmap needs
  • Lead technical design discussions, contribute to team decisions, and provide feedback on engineering approaches
  • Translate ambiguous technical challenges into actionable plans, and execute them in collaboration with the team
  • Serve as the cornerstone of our engineering culture by setting and upholding exemplary standards for code quality, practices, and craftsmanship

We're looking for someone who brings:
  • Experience working with security data problems
  • MS or PhD in a quantitative discipline is nice but certainly not required - strong bias for building product-informing experiments versus published works
  • 4+ years of experience designing experiments and managing data infrastructure
  • Understanding of both modern and classic machine learning techniques
  • Equally comfortable with Jupyter notebooks and building data pipelines
  • Seeks autonomy, creative problem-solving, and moving quickly in an ambiguous environment

Location: Hybrid role based in New York City. Some travel may be required.

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