Flex

Senior Staff Machine Learning Engineer

Flex

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

Visit company website
✨ AI Apply
Apply

Salary

💰 $188,000 - $225,000 per year

Job Level

Senior

Tech Stack

AWSAzureCloudGoogle Cloud PlatformKubernetesPythonPyTorchScikit-LearnSparkTensorflow

About the role

  • Drive development, deployment, and scalability of machine learning models in production environments.
  • Own the end-to-end lifecycle of machine learning projects, from data collection and preprocessing to model deployment, monitoring, and maintenance.
  • Build, maintain, and optimize robust data pipelines that support model development, training, and deployment at scale.
  • Implement machine learning algorithms and models that meet performance, scalability, and reliability requirements.
  • Collaborate with data scientists, engineers, and product teams to design and deploy ML systems that address business and product needs.
  • Continuously monitor and improve model performance, conducting experiments and tuning hyperparameters.
  • Leverage distributed computing frameworks and cloud platforms to process large-scale datasets efficiently.
  • Stay up-to-date with advancements in machine learning, software engineering practices, and deployment strategies.

Requirements

  • Master’s or Ph.D. in Computer Science, Engineering, or a related field.
  • 6+ years of experience as a Machine Learning Engineer, with expertise in building and deploying machine learning models in production environments.
  • Strong proficiency in Python, or similar programming languages, and experience with ML libraries like TensorFlow, PyTorch, and scikit-learn.
  • Extensive experience with cloud platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Spark, Kubernetes).
  • Proven track record of implementing end-to-end machine learning pipelines, from data preprocessing to production deployment and monitoring.
  • Strong background in model optimization, version control, and CI/CD practices for machine learning.
  • Excellent problem-solving abilities and the capacity to collaborate with cross-functional teams to deliver high-quality, production-ready systems.