Role overview

Member of Technical Staff, Machine Learning

Requirements and responsibilities

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Focus

  • Build and improve ML components across data, training, evaluation, and inference.
  • Fine-tune and adapt models as part of larger production systems.
  • Implement evaluation and testing to understand model behavior.
  • Help build and maintain data pipelines for real-world and synthetic data.
  • Debug model issues, performance problems, and production incidents.
  • Ship improvements iteratively and learn from real user feedback.
  • Work closely with senior ML engineers and product teams.
  • Work under real production constraints: latency, cost, reliability, and safety

Tech Stack

  • Python
  • PyTorch / JAX
  • Production ML systems running on GPUs

Ideal Experience

  • Strong foundations in machine learning and modern neural architectures.
  • Some hands-on experience training, fine-tuning, or deploying ML models.
  • Comfortable writing production-quality code and learning new tools quickly.
  • Curious, coachable, and eager to learn from real systems in production.
  • Able to work through ambiguity with guidance and grow ownership over time.
  • Bias toward shipping, iteration, and continuous improvement.

Outcomes

  • ML models in production meet expected accuracy, latency, and reliability targets.
  • Production issues are identified quickly, debugged effectively, and root causes addressed.
  • Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable.
  • Collaborates effectively with engineers, product, and research teams to deliver reliable ML-powered features.
  • Iterations on models and systems are driven by real-world signals and measurable improvements.
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Browse stack
FocusJunior Machine Learning EngineerRole area
Seniority signalJuniorCandidate level
StackPythonPrimary skills
Location1 accepted countryEligibility

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