मुख्य मजकुराकडे जा

Machine Learning Engineer (Mid-Level)

Overview
Cleragetclera.comPosted 11 days ago
San Francisco, CA, US$140k per yearकार्यालयातून
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वरिष्ठतेची पातळी
Mid
नोकरीचा प्रकार
पूर्णवेळ
कामाचा अनुभव
3+ years
विशेषीकरण
Machine learning & AI

भूमिकेबद्दल

Join a small, fast-moving team building AI-powered talent and recruiting technology. You will design, deploy, and maintain machine learning systems across the full lifecycle, helping turn product needs into reliable production capabilities.

Responsibilities

  • Design, train, and evaluate machine learning models for production use cases.
  • Build end-to-end ML pipelines, from data preprocessing through model serving and monitoring.
  • Work with product and engineering partners to translate business requirements into ML solutions.
  • Debug and improve models in production using monitoring data and real-world feedback.
  • Write maintainable code and contribute to ML infrastructure and tooling.
  • Participate in code reviews and share knowledge with teammates.

Key skills

  • Recruiting
  • Machine Learning
  • Python
  • TensorFlow
  • PyTorch
  • scikit-learn
  • AWS
  • Google Cloud
  • Kubernetes
  • Docker
  • A/B Testing

Benefits & perks

Base salary: $140,000 USD annually. Visa sponsorship information was not provided.

  • Company events

What We're Looking For

  • A degree and at least 3 years of professional machine learning or software engineering experience, including building and deploying production ML systems.
  • Strong understanding of model selection, evaluation metrics, feature engineering, and validation techniques.
  • Proficiency in Python and hands-on experience with TensorFlow, PyTorch, or scikit-learn.
  • Experience implementing production pipelines for data preprocessing, model serving, and monitoring.
  • Experience maintaining ML systems at scale with tools or platforms such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.
  • Experience with production A/B testing or experimentation frameworks.
  • Background working in fast-moving product environments and iterating on ML systems based on production feedback.

Location

On-site in San Francisco, California, United States.