Machine Learning Infrastructure Architect
3 days ago
Unreal Gigs Overview
Welcome to Unreal Gigs, a pioneering force in AI-driven innovation. We're committed to building robust infrastructure that powers our machine learning models at scale.
Salary: $195,000 - $255,000 per year
Position Summary
We're seeking a seasoned Senior Machine Learning Infrastructure Engineer to lead the design, development, and optimization of our machine learning infrastructure. As a key member of our team, you'll work on challenging projects, from building scalable data pipelines to deploying and managing machine learning models in production environments.
Key Responsibilities:
- Infrastructure Design: Design and architect scalable and reliable infrastructure solutions to support machine learning workflows, including data ingestion, model training, evaluation, and deployment.
- Data Pipeline Development: Develop and maintain data pipelines to ingest, preprocess, and transform data for training machine learning models, ensuring data quality, integrity, and scalability.
- Model Training Infrastructure: Build and optimize infrastructure for training machine learning models at scale, leveraging distributed computing frameworks and accelerators for performance and efficiency.
- Model Deployment: Design and implement systems for deploying and managing machine learning models in production environments, ensuring reliability, scalability, and real-time inference capabilities.
- Monitoring and Logging: Implement monitoring and logging solutions to track the performance and health of machine learning infrastructure and models, proactively identifying and resolving issues.
- Automation and Orchestration: Develop automation and orchestration tools to streamline machine learning workflows, reducing manual intervention and improving operational efficiency.
- Security and Compliance: Implement security controls and ensure compliance with data privacy regulations in machine learning infrastructure and workflows, protecting sensitive data and ensuring regulatory compliance.
- Documentation and Best Practices: Document infrastructure designs, processes, and best practices, providing clear and comprehensive documentation to facilitate understanding and collaboration among team members.
- Collaboration: Collaborate with data scientists, machine learning engineers, and software developers to understand requirements and deliver infrastructure solutions that meet business needs.
- Mentorship and Development: 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.
Benefits:
- 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.
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