Role overview

Founding Machine Learning Engineer

Requirements and responsibilities

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What You'll Do

  • Build and optimize end-to-end ML pipelines, from data ingestion to deployment.
  • Implement and fine-tune LLMs, embeddings, and generative models for real-world applications.
  • Develop efficient training and inference systems leveraging distributed compute.
  • Partner with data and product teams to translate ideas into measurable ML impact.
  • Contribute to model monitoring, evaluation, and continual learning frameworks.
  • Establish best practices in model versioning, reproducibility, and scalability.

What We're Looking For

  • 3–10 years of hands-on experience as an ML Engineer, Applied Scientist, or Research Engineer.
  • Proficiency in Python and at least one of PyTorch, TensorFlow, or JAX.
  • Experience building production-grade end-to-end ML pipelines (data ingestion, training, deployment).
  • Experience implementing and fine-tuning LLMs, embeddings, and generative models for real-world applications.
  • Hands-on experience with distributed training/inference and scalable ML systems.
  • Experience with cloud platforms (AWS, GCP, or Azure) and ML tooling (MLflow, Weights & Biases) for experimentation and model tracking.
  • Strong collaboration skills; ability to work cross-functionally with data and product teams.
  • Bias for action, autonomy, and eagerness to shape something from scratch.
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Browse stack
FocusFounding ML EngineerRole area
Seniority signalSeniorCandidate level
StackAWS, Azure, GCPPrimary skills
Location1 accepted countryEligibility

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