Responsibilities
You will architect and build shared training input pipelines from certified game capture to accelerators, covering storage layout, decoding, sharding, sampling, packing, batching, caching, prefetching, and host-to-device delivery across multiple training frameworks.
You will define schemas, data contracts, encodings, compression, and standards for dataset versioning, lineage, quality, coverage, acceptance criteria, and reproducible splits.
You will build deterministic loaders and checkpoint-safe iteration that recover from worker or hardware failures and corrupt data, including elastic restarts and changes to cluster size or parallelism.
You will design reproducible dataset mixtures and balanced batches across modalities, resolutions, sequence lengths, titles, and capture conditions, accounting for worker/rank locality and distributed parallelism.
You will benchmark and enforce throughput, data-wait time, step time, and accelerator utilization and stalls. Yu will model FLOPs utilization (MFU) where applicable, per-rank skew, scaling efficiency, restart time, reliability, and cost targets through thousands of accelerators.
You will diagnose bottlenecks and intermittent failures across storage, network I/O, CPU, memory, decoding, preprocessing, and accelerators, including stragglers, faulty hardware, corrupt samples, and imbalanced batches.
You will integrate compilers, runtimes, optimized kernels, low-precision training, and hardware-accelerated media processing. You will maintain efficient data delivery and recovery under FSDP/HSDP, tensor, context, and pipeline parallelism across heterogeneous accelerator environments.
You will lead training-pipeline architecture reviews, mentor engineers, and align priorities with research leads. You will translate model and data-access requirements into scalable systems building on shared infrastructure services, while researchers retain model-research ownership.
Qualifications
20+ years of development experience, including owning production systems for distributed-training input, with measurable improvements in throughput, accelerator utilization, step time, reliability, recovery time, or cost
Expertise building custom PyTorch training and ingestion systems or adapting TorchTitan, JAX/XLA with MaxText, Megatron Core/NeMo, or equivalent stacks for single jobs spanning thousands of accelerators
Expertise in FSDP2/HSDP, tensor/context/pipeline parallelism, mixed-precision training, and optimization on one or more accelerator platforms such as GPUs, TPUs, or AWS Trainium
Pre-training experience and an understanding of how model architecture, data representation, batching, and orchestration affect training-system design and efficiency
Expertise building large-scale multimodal streaming or hardware-accelerated ingestion with Ray Data, Mosaic Streaming, WebDataset, NVIDIA DALI, NVDEC, or equivalent technologies.
Deep knowledge of sharding, sampling, packing, caching, prefetching, deterministic data mixing, checkpoint-safe iteration, and elastic restart; experience with schemas, dataset versioning, lineage, quality, and reproducible training/evaluation
Experience profiling I/O, CPU, memory, network, distributed workers, and accelerators, including diagnosing cross-layer failures and intermittent faults
Pay Transparency - North America
COMPENSATION AND BENEFITS
The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs).
PAY RANGES
British Columbia (depending on location e.g. Vancouver vs. Victoria) *$204,600 - $287,500 CAD
California (depending on location e.g. Los Angeles vs. San Francisco) *$227,300 - $344,700 USD
Pay is just one part of the overall compensation at EA.
In the US, we offer a package of benefits including paid time off (3 weeks per year to start), 80 hours per year of sick time, 16 paid company holidays per year, 10 weeks paid time off to bond with baby, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) to regular full-time employees. Certain roles may also be eligible for bonus and other incentive programs.
For Canada, we offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and other incentive programs.
About Electronic Arts
We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.
We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.
Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.
