Location: Remote   |   Full-Time   |   $150,000 - $250,000
Machine Learning AI Python TensorFlow PyTorch Data Science AI Engineer Data Engineer

About Parable: Parable is an AI intelligence layer purpose-built for the C-suite, creating a holistic observability layer across entire organizations to drive real operating leverage. We help enterprise organizations of 1000+ employees gain unified visibility across their operations. Our platform enables data-driven decision-making and operational efficiency, with our experienced team achieving multi-million ARR in just six months.

Role Overview: We’re seeking Senior ML Engineers to join our growing team and help build cutting-edge AI systems that transform how enterprises manage their operations. You’ll work on challenging problems at the intersection of machine learning, data engineering, and business intelligence, creating solutions that drive measurable value for our customers.

Responsibilities:

  • Design, build, and deploy scalable ML models that power our observability platform
  • Collaborate with data scientists and engineers to define and implement machine learning solutions
  • Optimize existing ML systems for performance, accuracy, and cost efficiency
  • Conduct research on novel ML techniques and apply them to business problems
  • Mentor junior engineers and contribute to our technical leadership

Qualifications:

  • 5+ years of experience in machine learning engineering
  • Strong background in Python, ML frameworks (TensorFlow/PyTorch), and distributed systems
  • Proven track record of building production ML systems
  • Experience with MLOps and model deployment
  • Excellent problem-solving skills and ability to tackle ambiguous challenges
  • Passion for creating impactful AI solutions

What We Offer:

  • Competitive salary ranging from $150,000 to $250,000
  • Equity participation in our well-funded startup
  • Opportunities to work on challenging ML problems with real business impact
  • Collaborative environment with experienced engineers and data scientists
  • Remote-first culture with flexibility and distributed opportunities
  • Professional development and learning resources
Post Date: June 12, 2025