What You'll Do
Epic Games is looking for a Machine Learning Ops Engineer to support our machine learning classifiers used in content moderation and security. Your focus will be building reliable infrastructure for training, validating, serving, and monitoring our ML models at scale. This is an incredible opportunity to create a fun and safe environment for millions of players and make a positive impact on the entire Epic ecosystem.
In this role, you will
• Work directly with our ML engineering team to improve codebase architecture, performance, observability and scale.
• Operationalize proof of concept models into high availability production services, hosted on Amazon EKS, with a focus on factors such as latency, throughput and scalability.
• Build and optimize CI/CD pipelines to enable a team of 15+ engineers to ship ML models at scale, quickly and safely.
• Work with key stakeholders to identify technical debt and migrate legacy systems to the latest tools and platforms within Epic.
What we're looking for
• Experience with engineering, data analytics, and machine learning.
• Experience in building & maintaining technology used in ML development, with a focus on Python as the programming language.
• Experience in building and maintaining infrastructure for training and deployment of large-scale ML/DL models that scale across clusters with CPU/GPU machines.
• Experience in any of the following technologies & techniques is a plus: Pytorch, Torchserve, ONNX, Model quantization, TensorRT, OpenVINO, NVIDIA Triton.
• Fluency in Unix/Linux tooling, shell scripting and operating systems internal is a plus
• Excellent communication and interpersonal skills.
• BS/BA degree or equivalent work experience
Note to Recruitment Agencies: Epic does not accept any unsolicited resumes or approaches from any unauthorized third party (including recruitment or placement agencies) (i.e., a third party with whom we do not have a negotiated and validly executed agreement). We will not pay any fees to any unauthorized third party. Further details on these matters can be found here.
Jobcode: Reference SBJ-rzz49q-34-239-173-144-42 in your application.