JPMorganChase · 1 day ago
Distributed Training & Performance Engineer - Vice President
New York, NY
Full-time
Onsite
Entry Level
$164K/yr - $260K/yr
1+ years expJPMorganChase is a leading financial institution that offers innovative financial solutions. They are seeking a senior-level engineer to design, optimize, and scale large-model pretraining workloads across hyperscale accelerator clusters, focusing on distributed systems and performance engineering.
Asset ManagementBankingFinancial Services
Responsibilities
Design and optimize distributed training strategies for large-scale models, including data, tensor, pipeline, context parallelism
Manage end-to-end training performance: from data input pipelines through model execution, communication, and checkpointing
Identify and eliminate performance bottlenecks using systematic profiling and performance modeling
Develop or optimize high-performance kernels using CUDA, Triton, or equivalent frameworks
Design and optimize distributed communication strategies to maximize overlap between computation and inter-node data movement
Design memory-efficient training configurations (caching, optimizer sharding, checkpoint strategies)
Evaluate and optimize training on multiple accelerator platforms, including GPUs and non-GPU accelerators
Contribute towards incorporating performance improvements back to internal pipelines
Qualification
Required
Master's degree with 3+ years of industry experiences, or Ph.D. degree with 1+ years of industry experience in computer science, physics, math, engineering or related fields
Engineering experience at top AI labs, HPC centers, chip vendors, or hyperscale ML infra teams
Strong experience designing and operating large-scale distributed training jobs across multinode accelerator clusters
Deep understanding of distributed parallelism strategies: data parallelism, tensor/model parallelism, pipeline parallelism, and memory/optimizer sharding
Proven ability to profile and optimize training performance using industry standard tools such as Nsight, PyTorch profiler, or equivalent
Hands-on experience with GPU programming and kernel optimization
Strong understanding of accelerator memory hierarchies, bandwidth limitations, and compute-communication tradeoffs
Experience with collective communication libraries and patterns (e.g., NCCL-style collectives)
Proficiency in Python for ML systems development and C++ for performance-critical components
Experience with modern ML frameworks such as PyTorch or JAX in large-scale training settings
Preferred
Experience optimizing training workloads on non-GPU accelerators (e.g., TPU, or wafer-scale architectures)
Familiarity with compiler-driven ML systems (e.g., XLA, MLIR, Inductor) and graph-level optimizations
Experience designing custom fused kernels or novel execution strategies for attention or large matrix operations
Strong understanding of scaling laws governing large-model pretraining dynamics and stability considerations
Contributions to open-source ML systems, distributed training frameworks, or performance-critical kernels
Prior experience collaborating directly with hardware vendors or accelerator teams
Benefits
Comprehensive health care coverage
On-site health and wellness centers
A retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching
Company
JPMorganChase
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets.
10001+ employees
H1B Sponsorship
JPMorganChase has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
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Trends of Total Sponsorships
2025 (3471)
2024 (3469)
2023 (3395)
2022 (3594)
2021 (2515)
2020 (2495)
Funding
Current Stage
Public CompanyTotal Funding
unknown1998-02-01IPO
Leadership Team
Allison Beer
CEO of Card Services and Connected Commerce
Dan Mendelson
CEO, Morgan Health
Recent News
2026-01-23
2026-01-22
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