Software Engineer III - AI/ML Deep Learning & GPU ML Serving
Role details
Job location
Tech stack
Job description
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 Software Engineer III at JPMorgan Chase within the Commercial and Investment Banking team, you will be a key member of an agile team, designing and delivering secure, stable, and scalable technology products. You will implement critical technology solutions across multiple technical areas, supporting the firm's business objectives., * Develop, test, and troubleshoot software solutions, applying creative approaches to solve technical challenges.
- Write secure, high-quality production code and maintain algorithms integrated with firm systems.
- Produce architecture and design artifacts for complex applications, ensuring alignment with design constraints.
- Analyze and visualize large, diverse data sets to drive continuous improvement of applications and systems.
- Identify and address hidden issues and patterns in data to enhance code quality and system architecture.
- Collaborate with software engineering communities to explore and adopt new technologies.
- Participate in 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.
Requirements
- Formal training or certification on software engineering concepts and 3+ 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
- 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.
Benefits & conditions
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.