Senior Software Engineer I, ML Platform

Dandy

$120K — $150K *
US-AnywhereRemote in New York, NY
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience as a Machine Learning Engineer or Software Engineer in a high-growth startup environment.
  • Deep proficiency in ML Platform components like feature stores and distributed training.
  • Familiarity with Python-based ML frameworks (PyTorch/TensorFlow) and 3D Computer Vision is advantageous.
  • Extensive experience in large-scale data processing and building ML data pipelines.
  • Experience with automated build processes across diverse environments.
  • Strong knowledge of metrics, logging, and tracing for monitoring distributed systems.
  • Effective communication skills for discussing intricate architectural issues.

Responsibilities

  • Collaborate with ML Engineers to create ML training pipelines for massive 3D datasets.
  • Streamline the ML lifecycle by optimizing internal components and reducing technical debt.
  • Develop and maintain cloud-native systems and tooling in GCP/Kubernetes for 3D dental products.
  • Write clean, maintainable code and tests to uphold internal best practices.
  • Influence long-term architectural goals by partnering with stakeholders across the Engineering organization.

Benefits

  • Healthcare and dental coverage.
  • Mental health support resources.
  • Parental planning assistance.
  • Retirement savings options.
  • Generous paid time off.
Full Job Description


About the Role

In the past 3 years, Dandy has built the leading digital-first custom dental appliance manufacturer. As we move to the next level of scale, we are looking for a Senior Software Engineer to build the foundation of our ML Platform. You will be the bridge between SoTA Computer Vision research and production-grade reliability. You will design and scale the infrastructure that handles massive 3D datasets, orchestrates complex training pipelines, and ensures our generative models are deployed with high reliability.
What You'll Do
  • Collaborate with Machine Learning Engineers to build the ML training pipelines that process massive 3D datasets, orchestrate model training, and enable continuous model improvements.
  • Streamline the ML lifecycle, from data labeling and experimentation to deployment, by optimizing internal ML components and reducing technical debt.
  • Develop and maintain cloud-native systems and tooling (GCP/Kubernetes) that support Dandy's 3D dental products in a secure, well-tested, and high-performing manner.
  • Write clean, maintainable code and tests that set the standard for our internal best practices.
  • Partner with stakeholders across the Engineering organization to influence long-term architectural goals and maintain a high-quality bar.
What We're Looking For
  • 5+ years of experience working as a Machine Learning Engineer or Software Engineer, ideally within a high-growth startup environment.
  • Deep proficiency in building and maintaining ML Platform components, such as feature stores, model registries, and distributed training.
  • Experience with Python-based ML frameworks (PyTorch/TensorFlow) and experience with 3D geometric Computer Vision is a plus.
  • Deep expertise in large-scale data processing, with proven experience building ML data pipelines to empower complex model training.
  • Experience creating and maintaining automated build processes across multiple environments (e.g., Buildkite).
  • Strong background in implementing metrics, logging, and tracing to monitor complex distributed systems.
  • Ability to communicate concisely about complex architectural problems and propose iterative, pragmatic solutions.
  • New York City area candidates: Ability to work hybrid / 3 days a week at the company HQ in NYC


Req ID: J-962

For full-time positions, Dandy offers a wide range of best-in-class, comprehensive, and inclusive benefits tailored to each country where we operate. Our local benefits packages typically include healthcare, dental, mental health support, parental planning resources, retirement savings options, and generous paid time off-ensuring our team members are supported no matter where they live and work.

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