Machine Learning Engineer (Training Optimization)

Canva

21h

About The Position

As a Machine Learning Engineer, you’ll lead efforts to scale and optimize the training system for our large-scale multimodal and foundation models. You’ll design distributed training systems using Megatron-LM, NVIDIA NeMo, FSDP, and Triton—pushing the limits of performance across compute, memory, and communication layers. You'll sit at the intersection of systems and AI research, directly shaping how we train the models that will power Canva’s next generation of products.

Requirements

• We’re looking for a systems-first engineer who thrives in fast-paced, high-impact environments.
• You’re deeply familiar with distributed model training at scale and understand the nuances of optimizing compute at every level of the stack.
• You're excited by challenges that stretch current boundaries, and you’re a strong collaborator who communicates clearly across domains.
• Strong background in LLMs, multimodal AI, or diffusion models.
• Proficiency in Python.
• Deep knowledge of PyTorch or JAX as well as libraries such as Megatron-LM, NeMo, or DeepSpeed.
• Familiarity with common optimization techniques such as FSDP/ZeRO, gradient checkpointing, or low-precision data types.
• Hands-on experience writing custom GPU kernels in CUDA or Triton.
• Excellent communication and problem-solving skills, incl. full proficiency in English.

Nice To Haves

• Familiarity with a system programming language (e.g. C++ or Rust) is a plus.

Responsibilities

• You’ll design, implement, and optimize large-scale machine learning systems for training
• You’ll improve all aspects of performance, including GPU utilization, communication overhead, and memory efficiency.
• You’ll partner with research and modeling teams to align systems with algorithmic needs.
• You’ll evaluate and apply best practices for distributed training using industry-leading frameworks.
• You’ll dive deep into low-level optimization, including custom CUDA or Triton kernels.
• You’ll debug, profile, and fine-tune training workflows to unlock new levels of scalability.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: No Education Listed