Cloud Native Machine Learning Lead

3 weeks ago


San Francisco, California, United States Unreal Gigs Full time

We're seeking a Cloud Native Machine Learning Lead to join our team at Unreal Gigs. As a senior engineer, you'll be responsible for designing, developing, and optimizing our machine learning infrastructure, focusing on cloud-native solutions.

About the Role

You'll work closely with our data science team to understand their requirements and deliver infrastructure solutions that meet their needs. If you're a seasoned engineer with expertise in machine learning infrastructure technologies and a passion for building scalable, reliable, and efficient systems, we want you to join our team.

Responsibilities:
  • Design and architect scalable and reliable infrastructure solutions to support machine learning workflows, including data ingestion, model training, evaluation, and deployment, using cloud-native technologies.
  • Develop and maintain data pipelines to ingest, preprocess, and transform data for training machine learning models, ensuring data quality, integrity, and scalability.
  • Build and optimize infrastructure for training machine learning models at scale, leveraging distributed computing frameworks and accelerators for performance and efficiency.
  • Design and implement systems for deploying and managing machine learning models in production environments, ensuring reliability, scalability, and real-time inference capabilities.
  • Implement monitoring and logging solutions to track the performance and health of machine learning infrastructure and models, proactively identifying and resolving issues.
  • Develop automation and orchestration tools to streamline machine learning workflows, reducing manual intervention and improving operational efficiency.
  • Implement security controls and ensure compliance with data privacy regulations in machine learning infrastructure and workflows, protecting sensitive data and ensuring regulatory compliance.
  • Document infrastructure designs, processes, and best practices, providing clear and comprehensive documentation to facilitate understanding and collaboration among team members.
  • Collaborate with data scientists, machine learning engineers, and software developers to understand requirements and deliver infrastructure solutions that meet business needs.
  • Mentor junior engineers, sharing expertise and best practices in machine learning infrastructure engineering, and facilitate knowledge sharing sessions within the team.
Qualifications:
  • Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
  • 5+ years of experience in infrastructure engineering, with a focus on machine learning infrastructure.
  • Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Platform, and services like AWS SageMaker, Azure Machine Learning, or Google AI Platform.
  • Strong programming skills in languages such as Python, Java, or Scala, with experience in distributed computing frameworks like Apache Spark or TensorFlow.
  • Experience with containerization technologies such as Docker and container orchestration platforms such as Kubernetes.
  • Strong understanding of machine learning concepts and techniques, with experience deploying and managing machine learning models in production environments.
  • Strong problem-solving skills and analytical thinking, with the ability to design and troubleshoot complex infrastructure issues.
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
What We Offer:
  • A competitive salary: $190,000 per year, depending on experience and qualifications.
  • Comprehensive health, dental, and vision insurance plans.
  • Flexible work hours and remote work options.
  • Generous vacation and paid time off.
  • Professional development opportunities, including access to training programs, conferences, and workshops.
  • State-of-the-art technology environment with access to cutting-edge tools and resources.
  • Vibrant and inclusive company culture with opportunities for growth and advancement.
  • Exciting projects with real-world impact at the forefront of AI-driven innovation.


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