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Senior Software Engineer - Machine Learning

Celonis
New York, New York
Full Time
Posted January 12, 2026
$161k - $218k
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Job Description

A software engineer machine learning at Celonis is responsible for designing and developing AI and ML-based product features and infrastructure to enhance process intelligence solutions, working closely with cross-functional teams to deliver scalable, high-quality, and intelligent business process tools.

Key Responsibilities

  • Design and develop AI/ML product features and customer solutions
  • Understand business needs and translate them into technical AI/ML problems
  • Select appropriate AI/ML approaches for specific problems
  • Develop scalable and high-quality AI/ML models and approaches
  • Implement data collection mechanisms and evaluation processes
  • Build robust, low-latency infrastructure to serve AI/ML models
  • Create techniques to understand, represent, and integrate enterprise operational data
  • Develop APIs and infrastructure for scalable, low-latency data access
  • Ensure data freshness and accuracy across multiple enterprise customers

Requirements

  • Bachelor's degree, Master's degree, or equivalent practical experience in Computer Science or related fields with 3-5 years of experience
  • PhD degree in Computer Science or related fields with 1-3 years of experience
  • Strong communication and collaboration skills
  • Identify with the Celonis value of customer first, passionate about solving real world customer problems with a focus on finding the right solution regardless of the nature of the solution
  • Passionate about developing scalable and efficient AI ML solutions
  • Passionate about building high quality AI ML solutions with clear and repeatable evaluation mechanisms

Benefits & Perks

Base salary range: 161,000 - 218,000 USD (for New York location)
Total compensation package includes bonus, commission, equity, benefits, health, dental, life, 401k, and paid time off
Hybrid working options
Generous paid time off (PTO)
Company equity RSUs
Extensive parental leave
Dedicated volunteer days
Access to gym subsidies
Counseling and well-being programs
Clear career paths and internal mobility
Dedicated learning programs and mentorship opportunities
Global collaboration with international teams
Open culture with autonomous teams

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