Lead Software Engineer - Machine Learning

We have an opportunity to impact your career and provide an adventure where you

can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within AI/ML Data Platforms, you

are an integral part of an agile team that works to build and operate scalable,

reliable ML training systems and pipelines on AWS and other cloud platforms. You

will productionize training workloads (often GPU-based), improve performance and

cost efficiency, and enable repeatable, well-governed training across

environments.

Job Responsibilities

* Design, build, and maintain end-to-end ML training platform.

* Run and optimize GPU training workloads (single-node and distributed),

improving throughput, utilization and reproducibility.

* Build and operate training infrastructure on Kubernetes (e.g., EKS and other

manage Kubernetes platforms), including resource management and workload

troubleshooting.

* Enable Gen AI/LLM training and fine-tuning workflows (e.g., supervised

fine-tuning), including evaluation harnesses, artifact/version governance,

and scalable GPU execution patterns aligned to enterprise controls.

* Implement observability for training systems: metrics, logs, dashboards,

alerting, and operational runbooks.

* Partner with data engineering and platform teams to define interfaces,

standards, and guardrails (security, access, cost controls)

* Improve developer experience for training: standardized containers, CI/CD,

templates, documentation, and self-service workflow

* Drives team adoption of enterprise-authorized AI-assisted engineering

practices within the work environment to improve code quality, delivery

speed, and operational outcomes (e.g., AI-assisted code review/refactoring,

test strategy acceleration, incident/root-cause analysis support), while

establishing consistent validation standards (secure coding, peer review,

automated testing) and promoting reuse of effective patterns across the team.

* Applies knowledge of tools within the Software Development Life Cycle

toolchain, including enterprise-authorized AI-assisted development and

automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

* Formal training or certification on software engineering concepts and 5+

years applied experience.

* Demonstrated experience running ML training in cloud environments and

debugging issues across infrastructure & code.

* Strong Python skills with solid engineering practices (testing, code reviews,

modular design, dependency management).

* Experience building automation/CI for ML codebases (build, test, release,

deployment/promotion workflows).

* Hands on experience with deep learning training workflows and at least one

major framework (eg., PyTorch or TensorFlow).

* Understanding of training performance and stability: data loading

bottlenecks, mixed precision, checkpointing, reproducibility, and evaluation

methodology.

* Experience with distributed training and related concepts (e.g.,

DDP/FSDP/DeepSpeed concepts, collective communication basics, scaling and

bottleneck analysis).

* Ability to profile and optimize training systems (CPU/GPU utilization,

memory, I/O throughput, networking, scheduling).

* Experience with Kubernetes fundamentals for running compute-intensive

workloads and AWS (eg., EKS/ECR, S3, IAM, VPC/networking, Cloudwatch, EC2)

* Demonstrated experience leading effective use of approved AI-assisted

software development tools (e.g., for coding, code review, test acceleration,

troubleshooting) with the ability to set team expectations for validating AI

outputs for correctness, performance, and security.

* Strong understanding of responsible AI use in engineering workflows,

including data sensitivity considerations, secure handling of inputs/outputs,

and adherence to resiliency and security expectations; experience coaching

engineers on safe, compliant adoption within delivery practices.

Preferred qualifications, capabilities, and skills

* Experience running training workloads across multiple cloud platforms and

managing portability, performance, and governance across environments.

* Familiarity with cloud-native networking/storage patterns for high-throughput

training and artifact management.

* Experience optimizing training input pipelines (sharding, prefetching,

caching, format choices such as Parquet/WebDataset) and working with large

datasets.

* Familiarity with distributed compute frameworks (Spark, Ray, Dask) for

feature/dataset generation.

* Familiarity with workflow orchestration tools (Airflow-like systems, Argo

Workflows-like patterns) and model registry concepts.

* Experience optimizing training cost/performance (right-sizing, scheduling

policies, interruptible capacity strategies where applicable budge

guardrails, quota planning).

* Strong observability practice for training systems: metrics/logs/traces, GPU

telemetry, dashboards, and alert tuning.

FEDERAL DEPOSIT INSURANCE ACT: This position is subject to Section 19 of the

Federal Deposit Insurance Act. As such, an employment offer for this position is

contingent on JPMorganChase’s review of criminal conviction history, including

pretrial diversions or program entries.

JPMorganChase, one of the oldest financial institutions, offers innovative

financial solutions to millions of consumers, small businesses and many of the

world’s most prominent corporate, institutional and government clients under the

J.P. Morgan and Chase brands. Our history spans over 200 years and today we are

a leader in investment banking, consumer and small business banking, commercial

banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined

based on the role, experience, skill set and location. Those in eligible roles

may receive commission-based pay and/or discretionary incentive compensation,

paid in the form of cash and/or forfeitable equity, awarded in recognition of

individual achievements and contributions. We also offer a range of benefits and

programs to meet employee needs, based on eligibility. These benefits include

comprehensive health care coverage, on-site health and wellness centers, a

retirement savings plan, backup childcare, tuition reimbursement, mental health

support, financial coaching and more. Additional details about total

compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring

to our global workforce are directly linked to our success. We are an equal

opportunity employer and place a high value on diversity and inclusion at our

company. We do not discriminate on the basis of any protected attribute,

including race, religion, color, national origin, gender, sexual orientation,

gender identity, gender expression, age, marital or veteran status, pregnancy or

disability, or any other basis protected under applicable law. We also make

reasonable accommodations for applicants’ and employees’ religious practices and

beliefs, as well as mental health or physical disability needs. Visit our FAQs

[https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about

requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including

Disability/Veterans

Our professionals in our Corporate Functions cover a diverse range of areas from

finance and risk to human resources and marketing. Our corporate teams are an

essential part of our company, ensuring that we’re setting our businesses,

clients, customers and employees up for success.