Urgent AI Software Architect || Location: Burlingame, CA Or Pittsburgh, PA Heavily Preferred (Onsite)

Years of experience - 6+ years experience with Python and source control, 3+ years on PyTorch and DL

Must have Skills:

6+ years of experience in Python, especially with large codebases, preferably in Big Tech or mid-to-large companies

Experience in training big deep learning models with PyTorch

Proficiency in continuous integration and testing

Knowledge of code optimization techniques

Familiarity with GPU coding and backend ML systems (a plus)

Strong problem-solving skills and attention to detail, with the ability to independently overcome technical roadblocks

Experience working collaboratively and communicate effectively across functional teams

Capability to work independently and within a team

Experience in maturing machine learning systems, such as defining evaluation metrics, building evaluation systems, scaling up pipelines and tooling

Experience in creating and maintaining public projects (Github), Code Optimization (CPU and GPU), GPU Coding

Team / Role Overview

The XRCIA team aims at delivering the future of communication photorealistic telepresence via Codec Avatars. Our aspiration is to connect people separated by distance as if they were in the same room together. We achieve this by researching, developing and productionizing state-of-the-art methods in cross sections of computer

graphics, computer vision and machine learning for human understanding and telepresence. As a Research Engineer or Software Engineer on our team, the individual will have the opportunity to build innovative machine learning infrastructure that will shape the stability and robustness of cutting edge technologies that will power the

Metaverse.

Job Overview

We are looking for a seasoned Senior Software Engineer (SWE V) with a research engineering skillset to spearhead code improvement initiatives. The ideal candidate should possess a robust background in software development, particularly in Python, Deep Learning (DL) theoretical knowledge, experience training big DL models, and code

optimization. This includes continuous integration and testing, experience with GPU coding, PyTorch, and backend ML systems. Our team focuses on transforming DL research codebases into product-ready states.

Key Responsibilities

Codebase migrations

Enhancing code quality

Increasing test coverage through unit and integration testing

Code refactoring

Optimizing backend workflow orchestration

Additional engineering tasks such as setting up dashboards and alerts, and assisting with on-call workloads

Interact with scalable and distributed training algorithms and efficient data loading for large scale deep learning

Collaborate with both research and maturation teams to push research to products

Most of the tasks detailed would be performed on DL pipelines