What are the responsibilities and job description for the Lead Software Engineer - AI/ML Deep Learning & GPU ML Serving position at JPMorgan Chase?
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Banking team, you will play a pivotal role in an agile team, enhancing and delivering secure, stable, and scalable technology products. As a core technical contributor, you will drive critical technology solutions across multiple technical areas, supporting the firm’s business objectives.
Job Responsibilities
- Lead the design, development, and troubleshooting of software solutions, applying innovative approaches to complex technical challenges.
- Write secure, high-quality production code and maintain algorithms integrated with firm systems.
- Produce architecture and design artifacts for advanced applications, ensuring compliance with design constraints.
- Analyze and visualize large, diverse data sets to improve software applications and systems.
- Identify and resolve hidden issues and patterns in data to enhance code quality and system architecture.
- Collaborate with software engineering communities to explore and adopt emerging technologies.
- Guide system design and architecture discussions, focusing on reliability and scalability.
- Optimize deep learning models for production inference, including quantization and batching.
- Deploy and manage GPU workloads in Kubernetes environments.
- Build scalable, low-latency systems using web services and APIs.
- Partner with product and program management teams to deliver business-driven solutions.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5 years applied experience
- Professional software development experience, with emphasis on ML systems.
- Strong proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch, or similar).
- Experience with cloud technologies (Docker, Kubernetes, EKS) and public clouds (AWS, GCP).
- Hands-on experience with ML model serving frameworks (TorchServe, TensorFlow Serving, Triton Inference Server).
- Experience deploying and managing GPU workloads in Kubernetes.
- Familiarity with scalable, low-latency systems based on web services and APIs.
- Experience with NoSQL databases (Cassandra or equivalent) for high-throughput data access.
- Understanding of GPU resource management and cost optimization.
- Experience with modern microservices architecture.
- Ability to lead the design of large-scale systems and evaluate tradeoffs.
Preferred qualifications, capabilities, and skills
- MS/PhD in Computer Science, Machine Learning, or a related field.
- Proficiency in Java, Python, Scala, or C .
- Experience with graph neural networks and graph processing frameworks (DGL, PyTorch Geometric, NetworkX).
- Knowledge of GPU programming (CUDA) and performance optimization.
- Experience with model monitoring, A/B testing, and ML observability tools.
- Familiarity with MLOps tools and practices (MLflow, Kubeflow, SageMaker).
- Experience serving large-scale models and optimizing for performance.
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 JPMorgan Chase’s review of criminal conviction history, including pretrial diversions or program entries.