AI Engineer - MLOps (US)

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

At Gauss Labs we are looking for a passionate MLOps Engineer who will collaborate with scientists and engineers to improve manufacturing efficiency and reliability in IC manufacturing using data and artificial intelligence.

This role is responsible for automatically provisioning computational resources for our machine learning infrastructure. It is also responsible for implementing the mechanisms of automated error detection and recovery.

Responsibilities

• Implement training and inference infrastructure as code that can easily be deployed both on-prem and on different cloud service providers
• Deploy and configure platform automation to automatically scale training and inference infrastructure such that thousands of jobs can be run in parallel
• Implement health monitoring services and error recovery mechanisms
• Automate monitoring of platform performance to identify IO vs. compute bottlenecks
• Ensure inference pipelines meet very high availability requirements

Basic Qualifications

• BS, MS, or Ph.D. in quantitative fields (CS, Statistics, Math, or Engineering)
• 5+ years of work experience in MLOps
• Previous work has included cloud products (AWS, GCP, or Azure)
• Experience with containerization, Kubernetes, and Kubeflow
• Proficient in Python and ideally one other programming language
• Familiarity with REST and gRPC API design and implementation
• Prior experience with load testing tools such as locust or loader.io
• Knowledge of at least one built tooling system